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Volume 1 No.1 June, 2011
Copyright © ExcelingTech Publisher, United Kingdom
Web: excelingtech.co.uk ojs.excelingtech.co.uk/index.php/IJLTNC
Editorial Board Editor in Chief
Dr. Irfan Ullah, Middlesex University, London, UK
Managing Editor
Dr. Nida Aslam, Middlesex University, London, UK
Editorial Board Members
Dr. Imad Jawhar, Faculty of Information Technology, United Arab Emirates
University, UAE.
Dr. Natarajan Meghanathan, Department of Computer Science, Jackson State
University, Jackson
Table of Contents
1. Balanced Multiwavelet Based Mammogram Image Processing .............................................. 1
D.M.Garge, Dr.V.N.Bapat
2. Origin Authentication of Digitally Signed Message Using Joint Signature Scheme in
Mobile Commerce ................................................................................................................................ 6
Aihab Khan, Malik.Sikandar Hayat Khiyal, Sara Ayub
3. Non Repudiation in M- Commerce Using Joint Signature Scheme ............................... 13
Aihab Khan, Malik Sikandar Hayat Khiyal, Madiha Tariq
4. Design Issues and Applications of Wireless Body Area Sensor Networks.................... 19
Rakhshanda Yousaf, Sajjad A Madini, Aihab Khan
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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Balanced Multiwavelet Based Mammogram
Image Processing
D.M.Garge#1
, Dr.V.N.Bapat#2
#1 Lecturer in Electronics, Government Polytechnic, Kolhapur, India,
#2Principal, A.D. College of Engineering, Ashta, India,
1dattagarge@yahoo.com
2vbkanhaji@gmail.com
Abstract- This paper deals with the mammogram
image processing using balanced multiwavelets. The
property of balancing proves to be central to the
different issues ,like the preservation of smoothness in
images, improving the enrgy compaction ratio
etc.Using balanced multiwavelets, one can avoid the
steps of pre and post filtering, that is required with
systems based on unbalanced multiwavelets. Medical
researchers along with mathematicians and
technologists are working with mammogram images to
detect breast cancer at an early stage. Until recently,
the wavelet and multiwavelet theory has been applied
successfully in the domain of computer aided
diagnostics of cancer. However, the analytical
speculations indicate that the balanced multiwavelets
have great potential in mammogram image processing.
The present communication reports mammogram
image processing using balanced multiwavelets
implemented using MATLAB.
Keywords- Mammograms, Image Processing, Balanced
Multiwavelet, MATLAB
1. Introduction
Wavelet and multiwavelet transform is a useful tool
for signal processing applications such as image
compression and de-noising. Literature survey
reveals extensive work in the field of scalar wavelets
and multiwavelets. The latest entrant in the wavelet
paradigm are the „Balanced Multiwavelets‟. They
have several advantages such as smotthness in
scaling and wavelet functions, regularity of
multiwavelets, particularly significant in signal
processing applications; to name a few.[9] The
present paper describes implementation and
application of balanced multiwavelets for
mammogram image processing, which would play a
vital role in an early detection of the breast cancer.
We report here a simple method to generate
balanced multiwavelet of order one and two and its
application in image denoising. Experimental results
of application of balanced multiwavelets to
mammogram images have also been presented in
this paper.
While the authors have extensively dealt with the
mammogram image processing with multiwavelets
elsewhere [13], it is intended to present
experimental results regarding processing of
mammogram images using balanced multiwavelets
in the present communication.
The paper is organized as follows. At the outset, the
background information related to the breast cancer
is presented along with the literature review of
mammogram image processing techniques in
Section II. Section III describes the focus of present
work and section IV covers methodology adopted.
Section V summarizes theory of balanced
multiwavelets. At the end experimental results are
presented.
2. Literature Survey and Prior Art
Literature survey reveals that the mammograms and
their analysis by the way of image processing has
found to be on up-surge the interest of good number
of researchers. Being an interdisciplinary area of
research, there are contributions from many
disciplines such as statistics, mathematics, computer
and medical professionals and social scientists. The
role of application of statistical algorithm seems to
be dominating in this area.
The pioneering work in this area is done by Woods
K. S. et.al. [2] and Solka J. L. et. al. [3] in applying
the computer aided detection (CAD) of the Brest
cancer. Later, the techniques are refined by using
various methods such a heuristics, fuzzy reasoning,
Vector Space Machines, morphological approach
and use of adaptive wavelet transform, CAD
systems using filter banks etc. [4], [5], [6] The
research work seems to be forging on several
directions such as conceiving improved algorithms,
development of novel analytical framework,
development of custom hardware based on
programmable logic design etc.
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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3. Focus of the Present Work
In spite of great deal of research work in this area
briefly reviewed in section II, there are still
challenges lying ahead due to inherent limitations of
the scalar wavelets and multiwavelets. Some of the
limitations are difficulty in combining the
symmetry, orthogonality and second order
approximation. Multiwavelet processing requires pre
and post filtering of signal to be processed. Balanced
Muliwavelets offer possibility of superior
performance for mammogram image processing
applications as compared with scalar wavelets and
multiwavelets. Foundational work in
conceptualizing the Multiwavelet system is reported
by Geronimo, Hardin and Massopust (GHM) [7].
The basic technique of balanced multiwavelet has
been evolved in many directions. One of the major
directions is balanced Multiwavelet system with
higher order balancing as reported by Lebrun and
Vetterli (BAT01, BAT02).[9] Yet another
interesting piece of work in this field is Orthogonal
Balanced Multiwavelet (BAT 01); [14] that has
great potential for denoising mammograms. The
present work synergizes the above mentioned
techniques viz. GHM, BAT01 and BAT 02, to pave
the benefits of accurate classification of
mammograms. The advantages of our
implementation are evident from the results
compared with the traditional Daubechies scalar
wavelet (D4) used for the same purpose.
4. Methodology Adopted
Our methodology comprises of the following
sequence of steps:
a. Scaling functions and wavelets for first
order balanced and order 2 balanced multiwavelets
are implemented in MATLAB.
b. The test mammograms for processing are
taken from images available at
http://www.cancer.org [10]
c. The test images are decomposed and
reconstructed using wavelet, Multiwavelet and
balanced multiwavelet systems mentioned earlier.
Analytical measures like mean square error (MSE),
root MSE, distortion, signal to noise ratio and
energy compaction ratio (ECR) are used for
experimentation.
d. Then test images are mixed deliberately
with Gaussian noise, using function available in
MATLAB [11]. These noisy images are
decomposed by wavelet, multiwavelets and
balanced multiwavelets.
e. Images are reconstructed using
approximate coefficients only. Analytical measures
mentioned in step 2 are calculated.
5. Balanced Multiwavelets
It is possible to design orthonormal linear phase FIR
filter systems to construct multiwavelets. However,
prefiltering step turns out to be crucial when applied
to scalar valued data. To avoid prefiltering, concept
of balancing is introduced in [15] which is extended
to higher orders in [9]. Using these results, we have
constructed orthonormal multiwavelets of order 1
using filter coefficients shown in table I. Figure 1
and figure 2 show scaling and wavelets constructed
using these coefficients. In first order balanced
multiwavelet, scaling function is flipped around 1
and wavelets are symmetric / antisymmetric, the
length is three tap (2 X 2). In order 2 balanced
multiwavelet, scaling function is flipped around 2
and wavelets are again symmetris / antisymmetric,
the length is five taps (2 X 2).
Figure 1. BAT01 scaling function and wavelets
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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Figure 2. BAT02 scaling function and wavelet
Table 1. Coefficients of BAT01
Hk Gk k=0
0 2+√7
0 2+√7
0
-2
0
1 k=1 3 1
1 3 2 2
-√7 √7 k=2
2-√7 0
2+√7 0
-2 0
-1 0 factor 1/4√2 1/4
6 Metrics Defined In order to characterize the performance of the
system, certain benchmarking parameters are
required. This section formally defines all such
parameters. 5.1 Mean square error (mse)
[
( )]∑∑( ( ) ( ( ))
where S(x,y) is original mammogram image and
S‟(x,y) is denoised mammogram image.
5.2 RMSE = square root of MSE
∑∑( ( ) ( ( ))
5.3 Distortion = ∑ ∑ ( )
5.4 SNR = 1 / Distortion
5.5 ECR is defined as
ECR = ∑ ∑ ( )
∑ ∑ ( )
where S(x,y) is coefficient matrix of mammogram
consisting of approximate and detail coefficients,
and S^(x,y) is coefficient matrix with approximate
coefficients equal to zero.
5.6 Correlation as defined in MATLAB using
function corr2( ).
7 Results and Discussion
Figures 3 to 12 reveals the wavelet, Multiwavelet
and balanced multiwavelet based processing of
mammogram image. Figure 3 shows original
mammogram showing micro calcification. This
mammogram is decomposed and reconstructed
using D4 wavelet and multiwavelets as shown in
figures 4, 5, 6 and 7. Table 2 shows statistical results
obtained from these images. These results and
figures clearly indicate the superiority of the
balanced multiwavelets over the other wavelets for
accurate classification of mammograms. Energy
compaction ratio (ECR) also portrays more
information concentrated in low pass part of
Multiwavelet transform than in the low pass part of
wavelet transform as seen from table 2. Original
mammogram image is deliberately added with
Gaussian noise of mean average value zero, to create
noisy image as shown in figure 8. The subsequent
processed denoised images are shown in figures 9, 10,
11 and 12.
Figure 3. Original mammogram Figure
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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Figure 4. Mammogram reconstructed by D4
wavelet
Figure 5. Mammogram reconstructed by
GHM multiwavelet
Figure 6. Mammogram reconstructed by
BAT01 multiwavelet
Figure 7. Mammogram reconstructed by
BAT02 multiwavelet
Figure 8. Noisy mammogram
Table 2. Statistical results of
decomposition and reconstruction of image
Statistical
Measures D4 GHM BAT 01
BAT 02
MSE 9.0193 3.8018 3.6238 3.3454
RMSE 3.003 1.949 1.9036 1.829
Distortion 0.0039 0.0016 0.0015 0.0013
SNR 256.106 607.5764 666.676 769.237
Correlatio 0.9967 0.9986 0.9987 0.9991
ECR 0.0039 0.002 0.0036 0.0039
Figure 9. Denoised mammogram by D4
wavelet
Figure 10. Denoised mammogram by GHM
multiwavelet
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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Figure 11. Denoised mammogram by BAT01
multiwavelet
Figure 12. Denoised mammogram by
BAT02 multiwavelet
8 Conclusion
After reviewing recent emergence of multiwavelets,
we have examined the possibility of multiwavelets
in mammogram image processing, especially for
denoising application. We used simple method of
decomposition – reconstruction of image using
wavelet and multiwavelet transform to verify the
superiority of balanced multiwavelets. From above
results, it is seen that balanced Multiwavelets have
been proved to be superior to other wavelets, both
numerically and subjectively. Visually Multiwavelet
schemes seemed to preserve the edge better and
reduce Cartesian artifacts present in scalar wavelet
denoising. This work perhaps might be possibly
extended further in which other multiwavelets could
be applied to mammogram images to find out most
suitable multiwavelet for a particular mammogram.
References
[1] Gilbert Strang, “Short wavelets and matrix
dilation equations” IEEE transactions on
signal processing, vol. 43, No. 1, pp. 108-
115, January 1995.
[2] Woods, K.S.,et.al. “Comparative evaluation
of pattern recognition techniques for
detection of microcalcifications in
mammography”, International Journal of
Pattern Rece. and AI, vol 7, pp 1417-1436,
1993.
[3] Solka, J.L, et.al. “The detection of micro-
calcifications in mammographic images using
high dimensional features”, Proceedings of the
1994 IEEE seventh symposium on computer-
based medical systems, pp 139-145, 1994.
[4] Wan Mimi Diyana, et.al. “A comparison of
clustered microcalcifications automated
detection methods in digital mammogram”
IEEE ICASSP, pp. II385-388, 2003.
[5] Liyang Wei, et.al. “A study on several
machine-learning methods for classification of
malignant and benign clustered
microcalcifications” IEEE transactions on
medical imaging, vol. 24, no. 3, pp. 371-380,
March 2005.
[6] Ryohei Nakayama, et.al. “computer-aided
diagnosis scheme using a filter bank for
detection of microcalcification clusters in
mammograms”, IEEE transactions on
biomedical engineering, vol. 53, no. 2, pp. 273-
283, February 2006.
[7] J.S.Geonimo et.al. “Fractal functions and
wavelet expansions based on several scaling
functions”, J. Approx. Theory, vol. 78, pp. 373-
401, 1994
[8] C. K. Chui et. al. “A study of orthonormal
multiwavelets” J. Appl. Numer. Math., vol. 20,
pp. 272-298, 1996
[9] Jerome Lebrun, et. al. “High order balanced
multiwavelets: Teory, factorization, and
design”, IEEE transactions on signal
processing, vol. 49, no. 9, pp. 1918-1930,
September 2001
[10] Images of the breast cancer URL:
http://www.cancer.org Retrieved on February
14, 2009.
[11] MATLAB Version6.5, image processing
toolbox>functions
[12] Vasily Strela et. al. “The application of
multiwavelet filterbanks to image processing”,
IEEE transactions on image processing, vol. 8,
no. 4, pp. 548-563, April 1999
[13] D. M. Garge et. Al. “A Low Cost Wavelet
based Mammogram Image Processing for Early
Detection of Breast Cancer”, submitted to
Journal of Indian Science and Technology,
December, 2008
[14] Jian-ao Lian et. al “Balanced
multiwavelets with short filters”, IEEE signal
processing letters, vol 11, no. 2, pp 75 – 78,
February 2004
[15] Jerome Lebrun, et. al. “Balanced
multiwavelets: Teory and design”, IEEE
transactions on signal processing, vol. 46, no.
4, pp. 1119-1125, April 1998
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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Origin Authentication of Digitally Signed
Message Using Joint Signature Scheme in
Mobile Commerce
Aihab Khan, Malik.Sikandar Hayat Khiyal, Sara Ayub m.sikandarhayat@yahoo.com, aihabkhan@yahoo.com, rosaseae@gmail.com
Abstract—In this era of advanced technology, mobile
commerce has become popular due to rapid growth of
communication technology but this requires
maintaining secure communication and protection
from threats. In this paper, we presented a
mechanism for secure and authentic communication
in mobile commerce based on joint signature scheme.
We formulate this technique for the authentication of
message originator who signs the message to buy a
product online through its mobile operator. Proposed
technique is efficient in mobile domain because it is
less computative and can be used with limited
resources in mobile commerce. An experimental
analysis shows that proposed technique overcomes
the major drawbacks of traditional digital signed
message, such as computational load, communication
load, complexity, public key operations, transaction
etc.
Keywords—Joint signature, M-commerce, Origin
Authentication.
1. Introduction
The technology grows faster and faster, much
advancement is done in information technology
regarding communication, security, privacy etc. A
mobile device is a wireless communication tool,
including mobile phones, PDAs, wireless tablets,
and mobile computers. Mobile commerce (M-
commerce) can be defined as any electronic
transaction or information interaction conducted
using a mobile device and mobile networks, which
leads to transfer of real or perceived value in
exchange for information, services, or goods. M-
commerce offers consumers convenience and
flexibility of mobile services anytime and at any
place, and is playing an increasingly important role
in payments and banking [7].
Mobile communication is one of the prime aspects
of telecommunication and this aspect turns into
mobile commerce due to rapid growth of internet
and digital technology. Security in mobile
commerce is vital for its widespread usage.
Encryption/decryption techniques, digital signature
algorithms and other security measures are being
develop to secure the m-commerce channel.
Authentication is a process to identify a mobile
user, in order to authorize him/her to use system re-
sources for specified purposes. Authentication
involves negotiating secret credentials between
prover, and verifier for protecting communications
[1].Digital authentication systems become an
essential part of electronic payments via public
networks. These systems allow people and
organizations to electronically certify the
authenticity of an electronic document etc. Policies
associated with these systems, raise important
privacy and protection issues.
Digital signatures are based on certain types of
encryption policies to ensure authentication.
Encryption is the process of encoding data that one
computer is sending to another, into a form that
only the other computer will be able to decode [4].
Security is a crucial requirement of an m-
commerce system due to the fact that the sensitive
financial information that these systems transmit
travel over untrusted networks where it is
essentially fair game for anyone with local or even
remote access to any part of the path followed [5].
Joint signature scheme used in mobile commerce
for the secure transactions but it is not costly and
computationally low. Joint signature scheme is
based on hash functions and encryption/decryption
algorithms to produce joint signature with message
originator and message signer and also to
authenticate the message originator for message
signer and vendor (message verifier).This
technique is new and not much work is done in this
technique yet. Li-Sha HE et al[3] proposed joint
signature scheme for the authentication of mobile
user, but this technique is not implemented yet and
also its results are hypothetical [3]. We have
worked out on this technique and implement it for
the authentication of mobile user by its network
operator and vendor.
This paper is organized as follows. Section 2
elaborates related work and state of the art today.
Section 3 provides the frame work overview of the
proposed model. Section 4 discusses the technique
of the research model. Performance parameters are
discussed in Section 5 and Section 6 consist of
Conclusion and future work of this research.
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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In this paper we introduce a joint signature scheme
for the authentication of Mobile user in M-
commerce. Major contributions are as follows:
- To formulate an algorithm for authentication of
the origin of the message sent from a mobile user
so as to prevent any fraudulent actions by the
vendor or any other entities.
- To develop a model for authentication of the
signature of the signer that has sent a message.
- To ensure that the content of the message are
authentic and are being sent from the mobile user.
2. Related Work
Joint signature scheme is proposed by Li-Sha HE et
al [3] in 2004 ACM Symposium on Applied
Computing. This technique overcome the security
issues related to m-commerce e.g. authentication,
non-repudiation, confidentiality, integrity etc.But
this technique was not implemented at that time, so
we took this scheme as a base for the authentication
of origin of digitally signed message by the mobile
user for purchasing goods online. Very few works
is previously done for the authentication but
techniques which have been used for the
authentication have several drawbacks. Also these
techniques were based on traditional digital
signature scheme like Diffie Helmen which has
drawbacks in limited resources of mobile domain.
Server-aided technique proposed by Chin-Ling
Chen et al [7] for the mobile commerce uses trusted
proxy server to co-ordinate transactions between
user and vendor. It is based on the Diffie Helmen
scheme and involves the one-time password
mechanism to establish session key in advance
between user and vendor with the help of trusted
proxy server. This technique is divided into two
phases; negotiation phase and authentication phase.
This technique discussed different aspects of
security issues like anonymity due to high
communication load involves in negotiation and in
authentication phase communication between
mobile user and trusted third party.
Another technique proposed by Wooseok Ham et
al [6] secure one way payment system in mobile
commerce. This technique uses two modular
multiplications, one modular inverse and the
second is hashing by the user using two public key
pairs and keyed hash function for computation. In
this technique only unilateral communication is
sufficient between user and vendor to complete
payment. This technique has three main functions;
withdrawal, purchase and deposit. Also user does
not need to participate in deposit phase so
communication load and computation load is low
in this scheme. As more than one transaction is
involved so transaction overhead is present in this
scheme.
3. Framework Overview
The proposed framework for the authentication of
origin in mobile domain using joint signature
scheme is shown in figure 1.
Message
Originator (MO)
Message
Signer(MS)
Message
Verifier(MV)
Message
H (OAC)
H (OAC1)
Sign(Message,
H(OAC))
Key Distribution
Center
Shared
Secret Id
key K1
Shared
Secret Id
key K1 Shared
secret Id
key K2
Shared
secret Id
key K2
Secure
channel
Secure
channel
Secure
channel
Figure 1: Proposed Abstract model for origin authentication using joint signature scheme
In a proposed model as shown in fig 1, three main
entities are illustrated,
The message originator which is a mobile
station (MO).
Server run by the network operator signed
the message in its home environment(MS)
And service provider which verifies the
message and provides different services to
the mobile user (MV).
The shared keys are securely distributed between
these three entities. The message originator sends a
message along with H(OAC) and H(OAC1) to the
message signer which sign the message by its
private key and send it to the message verifier
which later on verifies the message and provide
authentication for the message originator.
The notations used in the model are given in table 1
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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Table 1: Notations
Notation Description
MO Message Originator
MS Message Signer
MV Message Verifier
H(OAC) Hash of Origin Authentication
Code between MO and MV
H(OAC1) Hash of Origin Authentication
Code between MO and MS
Id K1 Secret key shared between MO
and MV
Id K2 Secret key shared between MO
and MS
A detailed discussion of proposed abstract
model for origin authentication using joint
signature scheme is given in following section.
4. Technique
The abstract model of figure 1 elaborated by more
descriptive model is given below.
The Figure 2 explains as how message originator
MO produces the hash functions and sends it to the
message signer MS. Hash function H(OAC) and
H(OAC1) is produced on key Id K1 and Id K2
respectively, and message but with different keys
securely shared between these three entities.
Message signer MS signs the message and
produces the joint signature after verification of
message originator MO. After verification message
signer MS encrypts the message and sends it to
message verifier MV. Message verifier MV
decrypts the message and produces hash function
of its own and then after comparing both hash
functions provides the authenticity for the message
originator MO.
The process of origin authentication using joint
signature scheme consist of following four major
steps.
Step 1 :( Sharing Secret Key)
The message originator (MO) sends the message
and a shared secret key Id K1 to the message
verifier (MV) and produces a joint signature on
message with the help of message signer (MS) as
shown in fig 3.
M
Key
Distribution
center
Message
Originator(MO)
Message
Verifier(MV)
Secret
id K1
M
Secret
id K1
Secret
id K1
Figure 3: Distribution of secret keys between Message Originator and Message Verifier
M
M
----------
H(OAC)
----------
H(OAC1)H
H H(OAC)
H(OAC1)
llEp
Key
PRms
H(OAC)llH(OAC1)ll
M
Dp
Key
PUms
H(OAC)
--------
M
E(H(OAC)llM)
Id K2
Id K1
M H
Id K1
compare
Message
Originator(MO)
Message
Signer(MS)
Message
Verifier(MV)
------------------Joint Signature Generation---------------- ------Joint Signature Verification---------
H(OAC1)
H
compare
Secret
Id K1Secret
Id K2
Key
Distribution
Center
H(OAC)
Figure 2: Descriptive model of origin authentication using joint signature scheme
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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Step 2: (Produce Hash Function)
The message originator (MO) sends the message to
the message signer (MS) and produces a hash on
Origin Authentication Code H(OAC) and Origin
Authentication Code 1 H(OAC1) and sends it to
the MS with message. Also a Secret key Id K2 is
shared between MO and MS. Process is shown in
fig 4
M
H
H
ll
M
----------------
H(OAC)
----------------
H(OAC1)
H(OAC)
H(OAC1)
Key
Distribution
center
Message
Originator(MO)
Message
Signer(MS)
Secret
Id K2Secret
Id K1
Secret
Id K2
H
H(OAC1)
compare
Figure 4: Production of Hash function by Message Originator
The algorithm developed for producing hash
function is as follow:
Algorithm: Production of Hash function
Input: min, max, plaintext
Output: hash value
1.salt=random.next(min,max) //min and
max are integer values
2.plaintxtbytes=getbytes(plaintxt)
//converting from string to bytes
3.plaintxtwidsalt=plaintxtbytes+salt
//appending salt bytes
4. hash = SHA1 managed()
5.hashbytes= hash.computehash(plaintxtwidsalt)
//calculating hash value
6.hashvalue = convert.tobase64string(hashbytes)
//converting to string
Figure 5: Algorithm for producing hash function
Step 3: (Joint Signature Generation)
The message signer (MS) signed the message using
its private key on Hash Origin Authentication Code
H(OAC), a Hash Origin Authentication Code 1
H(OAC1) and message generated by the MO and
sends it to the MV as shown in fig 6.
Step 4 :( Origin Authentication)
The message Verifier (MV) decrypts the message
received from MS by public key of MS and verifies
the origin of the message by H (OAC) with the
help of message and shared secret key Id K1. And
MS verifies the H (OAC1) with the help of secret
key Id K2 shared between MO and MS.
The algorithm for the authentication of origin is
shown in Figure 7
Algorithm: Origin Authentication
Input: hash value
Output: verify hash for origin authentication
1.hashwidsaltbytes=convert.frombase64string(hash
value) // converting to bytes
2. if(hashwidsaltbytes.length < hashsizeinbytes) then
3. verify hash = false
4. end if
5. for I = 0 to saltbytes.lendth-1
//saltbytes is a difference between
//length of hashsizebits and hashsizebytes
6.saltbytes(I)= hashwidsaltbytes(hashsizeinbytes)
7. next I
8.expectedhash=computehash(plaintext,saltbytes)
// computing hash values to verify
9. verify hash = (hash value = expectedhash)
// comparing hash values
Figure 7: Algorithm for Origin Authentication
The above steps can also be elaborated sequentially
by using sequence diagram in fig 8 as:
M
------------------
H(OAC)
Ep
Key
PRms
H(OAC)llM
Dp
Key
PUms
HOAC
-----------------
M
E(H(OAC)llM)
Message
Signer(MS)
Message
Verifier(MV)
Figure 6: Joint signature generation by
Message Signer
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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Message Originator Message Signer Message Verifier
Sends shared secret key
k1
Send message to buy
Sends shared secret key
k2
Send message
Send hash of message
and its origin along with
message Verify hash of message by
k2
Encrypts the message and
hash of message origin by
own private key
Send encrypted message
Produce the hash on
given message by
using key
Verify the hash on
origin of message
with the produced
hash
Authenticate the Message Originator
Decrypt the
message by MS
public key
Figure 8: Sequence Diagram of working of model for Joint signature Origin Authentication
5. Performance Results
Performance of proposed technique is analyzed on
parameters like computational load,
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
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communication load, complexity, public key
operations, transactions with respect to other
techniques and following observations were made.
Table 2: Performance measure of proposed Technique
Computational
Load
Joint Signature Scheme
(Proposed Scheme)
Server Aided Signature
Scheme
Secure one way mobile payment
Scheme
In this scheme two hash function and one public key
operation is used in
computation which is very efficient in limited resources
so computational load is Low in this scheme
Proxy server or trusted third party is
involved in this scheme which performs
complex operations, based on traditional digital signature scheme like Diffi
Helmen which bears more computational cost in limited resources
so computational load is High in this
scheme.
One modular inverse, two
modular multiplications and two
hash functions are involved in computation which can
effectively be implemented in
mobile domain with limited resources. Also no
exponentiation calculations are involved that are used in RSA
and a Diffi Helmen technique,
so computational load is Low.
Communication
Load
In this scheme only one
transaction is done from customer to the network
operator so communication
load is Low in this scheme.
Two way Communications are involved in negotiation phase and in
authentication phase so more than one
transaction is involved in this scheme so communication load is High in this
scheme.
In this scheme customer does not
need to be involved in deposit
phase, so unilateral communication is done between customer and
vendor to complete payment
transaction. So communication load is Low in this scheme
Complexity
In this scheme only one
public key operation is performed at service provider
to verify the joint signature
by network operator so public key operation is Low
in this scheme.
Two public key operations are involved in
this scheme, one to verify secret from original signer by public key of trusted
third party and second to verify signature
by public key of signature signer. So public key operations in this scheme is
High.
In this scheme customer has two
private and public key pairs for
signing and verification. So two public key operations are involved
in this scheme, so public key
operation is High in this scheme.
Transactions
In this scheme only one
transaction is required from
customer to network operator
so transaction in this scheme is Low
In this scheme two transactions are required
between original signer and signature signer in negotiation and authentication phase so
transaction in this scheme is High.
In this scheme more than one
transaction is required in
withdrawal, purchase and deposit
phase so transaction in this scheme is High.
Experimental analysis shows that joint signature is
much efficient and less complex than others
schemes with low computation and communication
load is which is very useful in mobile commerce as
in mobile commerce resources are very limited as
compare to other domains like banking, online
purchasing etc, so joint signature scheme is
efficient and can be used in mobile commerce for
origin or client authentication. The comparison is
shown in table 3.
Table 3: Comparison Analysis
Techniques Computational Load Communication Load Public key
operations Complexity Transactions
Joint Signature
scheme Low Low Low Low Low
Server-aided
Signature
Scheme
High High High High High
Secure One-way
Mobile Payment Low Low High Low High
Proposed
Scheme Low Low Low Low Low
6. Conclusion And Future Work
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
12
In this paper, we have presented a novel joint
signature scheme for the authentication of origin of
message that is digitally signed by the mobile user
(message originator) with the help of its network
operator(message signer),both jointly produce the
signature which is going to be verified by the
vendor(message verifier).Authentication is done on
both entities i.e. message signer and message
verifier which proved them that the message
originator is the right person who sends message to
vendor. Furthermore this technique is more
efficient than other traditional schemes which are
used for authentication in mobile commerce. In
comparison with existing techniques mainly server
aided scheme and secure one way mobile payment
mechanism, this technique overcomes all major
disadvantages of existing techniques.
In future, it is recommended to extend joint
signature scheme for the authentication of message
that is digitally signed by the user in order to avoid
any fraud over the transmission line. Moreover this
technique can be implemented for other security
issues like confidentiality, integrity, non-
repudiation etc.
References [1] Babu.S.B, Venkataram.P, 2009, “A Dynamic
Authentication Scheme for Mobile Transactions”, Protocol
Engineering Technology (PET) Unit, Department of Electrical
Communication Engineering Indian Institute of Science,
Bangalore, 560 012, India (Email: fbsb,
pallapag@ece.iisc.ernet.in) International Journal of Network Security, Vol.8, No.1, PP.59-74, Jan. 2009
[2] Chen C-L, Chen C-L, Liu L-C, Horang.G, 2007, “A Server-
aided Signature Scheme for Mobile Commerce”, Department
of Computer Science and Information Engineering, Chaoyang
University Technology,Taichung,Taiwan.clc@mail.cyut.edu.tw, Department of Mechatronics Engineering, National Changhua
University of Education Changhua, Taiwan 500, ROC.
d95631003@mail.ncue.edu.tw, Department of Computer Science, National Chung Hsing University , Taichung, Taiwan
402, ROC.0287@sun.epa.gov.tw, , Department of Computer
Science, National Chung Hsing University , Taichung, Taiwan 402, ROC. gbhorng@cs.nchu.edu.tw. IWCMC'07, August 12-
16, 2007, Honolulu, Hawaii, USA.
[3] He L.S, Zhang.N,(2004), “A New Signature Scheme:
Joint-Signature”, Department of Computer Science the
University of Manchester, Manchester UK, 0044-161-2756270 {hel, nzhang}@cs.man..ac.uk, SAC’2004, March 14-17, 2004,
Nicosia, Cyprus.
[4] Kadhiwal.S, Usman.M.A, 2007, “Analysis of mobile
payment security measures and different standards”,
Shaheed Zulfiquar Ali Bhutto Institute of Science and Technology, Karachi, Pakistan.
[5] Kritzinger.F, Truter.D,(2003) , “A Secure End-to-End
System for M Commerce: Research Paper CS03-24-00”, October 12, 2003.
[6] Ham.W, Choi.H, Xie.Y, Lee,M, Kim.K, „Secure One-way
Mobile Payment System Keeping Low Computation in
Mobile Devices‟, International Research center for Information Security (IRIS) Information and Communications University
(ICU) 58-4 Hwaam-dong, Yusong-gu, Daejeon, 305-732, S.
Korea, School of management Information and
Communications University (ICU).
[7] Nambiar.S, Lu.C-T, Liang.L.R, 2008 “Analysis of Payment
Transaction Security in Mobile Commerce‟, Department of Computer Science Virginia Polytechnic Institute and State
University 7054 Haycock Road, Falls Church, VA 22043
{snambiar, ctlu}@vt.edu, Department of Computer Science University of the District of Columbia Washigton, DC 2008,
lliang@udc.edu.
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
13
Non Repudiation in M- Commerce Using
Joint Signature Scheme
Aihab Khan, Malik Sikandar Hayat Khiyal, Madiha Tariq
aihabkhan@yahoo.com, m.sikandarhayat@yahoo.com
Abstract—Being the hottest issue of today’s time there
as a lot of work to be done on mobile commerce .in
mobile commerce mobile is used to avail a lot of
services. One of these services includes online
purchasing of different items. Mobile subscribers can
by items anywhere at any time by using their mobile.
The bills are compensated by their network operators.
Different security issues are involved during such
transactions. One of the issues that of non-
repudiation. This service prevents the sender and
receiver to deny their participation in the transaction
and to ensure the integrity of the message. This paper
represents the mechanism for non-repudiation in m-
commerce using joint signatures. This mechanism is
based on the use of hash functions and traditional
digital signatures where network operators have
trusted third party or an arbitrator to satisfy this
requirement. This mechanism is efficient to be used in
mobile domain having less resource due to low
computation and communication load. Also it is
simpler than traditional digital signature scheme. We
formulate this approach to overcome the problem of
non-repudiation in mobile domain.
Keywords—Authentication, Joint Signatures, Mobile
commerce, Non-repudiation.
1. Introduction
Internet is used to share information along different
channel. This information is shared along multiple
channels through internet protocol security
(TCP/IP).Network security consists of several
provisions in computer network infrastructure,
policies to protect their network from illegitimate
user and continuous monitoring of network.
1.1 M-Commerce verses E-Commerce
M-commerce is unique from e-commerce having a
show function. There are some similarities between
m-commerce and e-commerce but as a whole m-
commerce is different from e-commerce.
“Mobile commerce is any transaction, involving
the transfer of ownership or rights to use goods and
services, which is in initiated and/or completed by
using mobile access to computer-mediated
networks with the help of an electronic device.”
When data is travelling over the network it needs to
be protected. A lot of security features should be
incorporated for the secure m-commerce for
security reasons a lot of techniques like digital
signatures, hash functions, encryption etc. are used.
Digital signature is a type of asymmetric
cryptography. It helps the receiver to make sure that
message is send from legitimate users.
1.2 Digital Signatures in m-communication
Existing digital signature schemes are costly to be
used in m-commerce. Digital signature generation
is most time and resource consuming operation to
be performed by mobile devices. Different
asymmetrical payment methods have been
developed for mobile users to buy goods online.
These methods require less resource to perform the
transactions but there is a major problem with these
approaches that network operator may abuse the
trusts. Therefore these approaches must be outfitted
with a strong security level so that everyone
involved in the transactions should be accountable.
As digital signature generation is computationally
expensive for a mobile device, which has
considerably less computing resources then a
desktop, so another scheme may b used i.e. joint
signature scheme [7].The model presented in this
paper is derived from the research work of Li-Sha
HE et al that was presented in ACM Symposium on
Applied Computing in 2004.in there research they
have presented a model for implementing joint
signature schemes in m-commerce. Here three
entities are involved. The originator generates the
message and applies hash on message with shared
secret id key K1 and K2 and sends the message
along with two hash values (joint signatures) to the
signer. The signer signs the joint signature with its
private key and sends this signed joint signature to
the verifier where verifier decrypts to authenticate
the origin this model is a hypothetical model that is
not implemented. Our research is based on the
implementation of this model along with addition
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
14
of some security services may have developed a
mechanism for implementing non-repudiation of
both sender and receiver in m-commerce using
signature scheme and incorporated our mechanism
to their hypothetical model and also implemented
there model. This research is intended for
implementing non-repudiation in m-commerce
using joint scheme. Objective of this research is to
develop a mechanism for non-repudiation in m-
commerce scheme. This mechanism caters the
prevention of denial from sender and receiver about
their participation in the transactions and ensures
the integrity of the message. The proposed
mechanism is applicable in mobile domain with
limited resources. The reminder of this paper is
organized as .In section 2 named as ‘Related Work’
brief discussion of different signature scheme is
represented. In the section 3 ‘Proposed Framework
Model’. Our proposed model is described. The
explanation of our proposed model is given in
section 4 ‘Technical Description of Proposed
Model’. In the section 5 ‘Performance Results’ the
performance of our proposed mechanism is
discussed. Section 6 as conclusion is followed by
the ‘Future Work’
2. Related Work
In this section we introduce three important
signature schemes proposed by Li Sha HE et al [1],
Ching-ling Chen et al[2] and Guilin Wang et
al[3].Joint signature scheme [1] is an extension of
digital signature scheme as this scheme is based on
the use of hash functions and traditional digital
signatures. In joint signature scheme there is no
concept of proxy signer and only one public key
operation is involved so there is less
communication and computational overhead. In
mobile domain there are limited resources so this
scheme is efficient to be used in mobile domain.
Digital signature scheme is used where there is
large number of resources hence on mobile domain
with limited resources using digital signature
scheme is not that much efficient. Server aided
signature scheme [2] involves hash functions and
traditional digital signature scheme. Here signature
server is required, signature server and original
signer require a round trip-communication.
Signature server verifies the signature on received
public key. In this technique there is a computation
and communication overhead for signature
generation. Hence time required to generate a
signature is increased. Due to all these reasons this
technique is not efficient to be used in mobile
domain. In proxy signature scheme [3] the proxy
signer is introduce to produce a digital signature on
behalf of the original signer. Proxy signature
scheme has three categories named as full
delegation, partial delegation and delegation by
warrant. In full delegation the proxy signer signs
the message with original signer keys, in partial
delegation new proxy key is generated from the
original key by the original signer and sent to the
proxy signer. Proxy signer then uses this proxy key
for purpose of signature generation. In delegation
by warrant there is higher processing overhead as
original signer has to sign certificate with its private
key. This scheme also has higher processing
overhead and high communication and computation
load. In this paper we introduce several security
services as authentication, message integrity, and
non- repudiation in m-commerce to a scheme
named as joint signature scheme. Other security
services like confidentiality etc can also be
implemented using this scheme.
3. Proposed Framework Model
Key Distribution
Center
Network operator
(NO)Message sender
(S)
Service Provider
(SP)
Secure channel Secure channel
Secure channel
Shared id key K1
Shared id key K2Shared id key
K1
Shared id key K2
Message
HOACSSP
HOACSNO
Sign message
HOACSSP
HOACSNO
HOACSSP
Figure 1: Framework Model
The proposed framework model shown in fig 1
explains that key distribution center distributes the
key with the message sender(S), network operator
(NO) and the service provider(SP).message
sender(MS) sends a message, compute hash of it by
using shared key and send it to NO.NO signs the
message, verifies it, and send it to SP.SP then
verifies that non repudiation is not occurring by
using its shared key.
Description of the terms involved in proposed
model are given below:
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
15
Table 1 Notations
S Message sender
NO Network operator
SP Service provider
M Message being sent by the message
sender
K1 Shared id key between message
sender and network operator
K2 Shared id key between message
sender and service provider
H Used for hash function
|| Sign of concatenation
PRNO Private key of network operator
PUNO Public key of network operator
HOACSSP
Hash origin authentication code
between sender and service
provider
HOACSNO
Hash origin authentication code
between sender and network
operator
EP Public key encryption
DP Public key decryption
4. Technical Description of Proposed Model
Technical description of the proposed model Is
given below:
Step 1:
The message sender(S) sends the message to
service provider (SP) and produce a joint signature
on message with the help of network operator.
(NO)
Step 2:
The network operator (NO) signs the message
using its private key on hash origin authentication
code between sender and service provider
HOACSSP, a hash origin=n authentication code
between sender and network operator (HOACSNO)
and message, NO will also verify the hash function
in order to verify that the message is actually sent
from the legitimate sender i.e. origin authentication.
Also it verifies HOACSNO for the sake of message
integrity and origin authentication. Once the origin
is authenticated it cannot deny its participation in
the transaction. It is done for the non-repudiation of
the origin.
Step 3:
The service provider (SP) decrypts the message
Figure 2 :Proposed Model
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
16
using NO’s public key to authenticate the network
operator. Network operator cannot deny its
participation in the transaction. Also it verifies the
message for the message integrity by comparing the
message from NO to the message sent by the
sender. SP will also verify hash function in order to
verify that the message is actually sent from the
legitimate sender .i.e. origin authentication.
Step 4:
The service provider (SP) after receiving
HOACSSP from the network operator (NO) will
send it back to the NO in order to get authenticated
by the network operator. Once the SP is
authenticated it cannot deny its participation in the
transaction. It is done for the non-repudiation of the
receiver.
In the above shown fig 2, message sender (MS)
sends a message, compute hash by using keys, and
then concatenated message to these is send to NO.
Till here joint signature is generated. Then NO
encrypts
This concatenated message by using its private key.
At SP end this encrypted message along with hash
is decrypted by using public key of No. At SP end
the original message and hashes i.e HOACSNO and
HOACSSP is compared to verify non repudiation
Step 1 (sharing secret key)
Key distribution center distributes the secret shared
id key K1 and secret shared key K2 among the
message sender (S),network operator(NO) and the
service provider.K1 and K2 are sent to the message
sender through a secure channel also K1 is sent to
the NO and K2 is sent to the SP through secure
channel by key distribution center. This is shown in
fig 3.
Step 2 (Message Generation)
Message sender generates the message and sends
this message to the service provider (SP) as well as
network operator (NO).
Step 3 (Production of hash on Message)
The message sender (S) generates message and
produces HOACSNO, Hash Origin Authentication
code between the sender and network operator and
HOACSSP. Hash origin authentication code
between sender and service provider with the help
of shared secret key K1 and K2 respectively on
message and sends both HOACSSP and
HOACSNO to the network operator (NO) as shown
in fig 4.
Step 4 (Joint Signature Generation)
Figure 3
Figure 4
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
17
The network operator (NO) signs the message
using its private key on HOACSSP, HOACSNO
and message generated by the S and sends it to the
Service provider (SP).this shown in fig 5.
Start
end
Message ||
HOACSSP ||
HOACSNO
received
Send encrypted
message to the
other server
Encrypt using
its private key
Figure 5
Step 5(Authentication)
The service provider (SP) decrypts the message
received from NO by public key of NO and verifies
the origin of the message by HOACSSP with the
help of message and shared secret id key K1.this is
done on order to cater the non-repudiation of origin.
NO verifies the HOACSNO with the help of shared
secret id key K2 between S and NO as shown in fig
6.
Start
end
Encrypt
Message ||
HOACSSP ||
HOACSNO
received
Decrypt using the
other server’s
public key
Figure 6
Step 6(Non-Repudiation)
The service provider (SP) when decrypts the
message that is sent from NO gets HOACSSP.SP
sends this HOACSSP back to the NO for the
purpose of its authentication. This is a concept on
hand shaking which is implemented in order to
cater the non-repudiation of receiver. This is shown
in fig 7.
start
end
Send HOACSSP
to network
Operator
Verification by
network
operator
Service
provider
Authenticated
Figure 7
5. Performance Results
The results demonstrate that joint signatures cam be
efficiently used in m–commerce.
Computational load
In proposed scheme two hash functions are used for
computation, and hash function can easily
implement in mobile domain with limited resources
so in proposed scheme computational load is low.
Communication Load
In propose scheme only one transaction is required
from message originator to message signer for
producing joint signature so in proposed scheme
communication load is low.
Public key operations
In proposed scheme only one public key operation
is required by message verifier to verify the joint
signature from message signer. So in proposed
scheme public key operation is low.
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
18
Complexity
In proposed scheme trusted third party is no
involved (NO is behaving as a trusted third party)
in communication so proposed scheme is less
complex than other schemes.
Transactions
In proposed scheme one transaction is done
between message originator and message signer for
producing joint signature scheme so in proposed
scheme transaction overhead is low. Thus joint
signature scheme is much efficient and less
complex than other scheme, in joint signature
scheme computation and communication load is
low which very useful in mobile commerce as
resources are limited in mobile domain as compare
to other domains like banking, online purchasing
etc, so joint signature scheme is easy and effective
and can be used in mobile commerce for
authentication non-repudiation and message
integrity.
6. Conclusion and Future Work
In this paper we have presented a mechanism for
non-repudiation in m-commerce using joint
signature scheme. In situations where there is not
complete trust between sender and receiver
something more than authentication is needed.
Basically it is the need of non-repudiation. The
mechanism that we have presented is a type of
arbitrated digital signature. Our mechanism gives
an efficient solution to the problem of repudiation.
In order to make the transactions securer inclusion
of this feature is very important. The reason due to
which we selected joint signatures for
implementing non-repudiation in m-commerce is
that in mobile domain we have limited resources.
Joint signature scheme best fits in the domain
having fewer resources. Also this scheme is more
efficient than the existing scheme as it involve less
public key operations and transactions. Due to this
reason the scheme is simpler and less expensive.
For future we’ve planned to work on other security
issues like confidentiality etc. to incorporate in this
scheme.
References
[1] Li-Sha He, Ning Zhang, "An Asymmetric
Authentication Protocol for M-Commerce
Applications," Eighth IEEE Symposium on
Computers and Communications, ISCC, pp.244,
2003
[2]Ching Ling Chen et al ‘A Server-aided
Signature Scheme for mobile commerce’,
Department of Computer Science and Information
Engineering, Chaoyang University of
Technology,Taichung,2007,Taiwan.clc@mail.cyut.
edu.tw
[3]Guilin Wang et al ‘Proxy Signature Scheme
with Multiple Original Signer for Wireless E-
Commerce Applications’, Infocomm Security
Department, Institute for Infocomm Research
(I2R),2004
[4]Chung et al ‘Adaptation of proxy certificates
to non-repudiation protocol of agent-based
mobile payment systems’, Springer Science
Business Media, LLC 2007
[5]Chin et al ‘A fair and secure mobile agent
environment based on blind signature and proxy
host’, Department on Computer Science and
Information Management, Providence University,
Department of Computer Science and Information
Engineering National Chung Cheng
University,2004
[6] Jonker ‘M-commerce and M-payment
combining technologies’, 2003
[7] http://en.wikipedia.org/wiki/Mobile_commerce
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
19
Design Issues and Applications of Wireless
Body Area Sensor Networks
1Rakhshanda Yousaf,
2Sajjad A Madini
3Aihab Khan
1,2Comsats Institute of Information Technology, Abbottabad, Pakistan
3Fatima Jinnah Women University, Rawalpindi, Pakistan
rakhshee@gmail.com, madani@ciit.net, aihabkhan@yahoo.com
Abstract— A body area network connects together
different nodes attached to human body and then to
an external station and sometimes to internet.
Different network topologies are used according to
the requirement of application. Wireless body area
networks offer many promising new applications in
the area of remote health monitoring, sports, and
military etc. BANs are faced with many research
challenges as this area is still thought of being in its
infancy. These challenges include channel mode
selection, antenna design, physical and MAC layer
protocol design, and many more. Bluetooth, Zigbee,
ANT, Sensium, Zarlink etc are some of the candidate
wireless technologies that conform to the needs of
BANs. Conflicts between requirements of BANs also
need to be addressed, these conflicts exist among
requirements like security, efficiency, safety etc.
Continuous monitoring of wireless users is very
important because they may get stuck in any critical
condition. This work address all these issues in detail.
Keywords— body area networks (BANs), body sensor
networks (BSNs), wireless body area networks (WBANs),
wireless networks, wireless sensor networks (WSNs).
1. Introduction
A Body Area Network is formally defined by IEEE
802.15 as, "a communication standard optimized
for low power devices and operation on, in or
around the human body (but not limited to humans)
to serve a variety of applications including medical,
consumer electronics / personal entertainment and
other" [IEEE 802.15].The term BANs will be used
as shorthand for body area networks in the rest of
text.
A body area network connects self-regulating
nodes attached to the body surface, implanted in
the body, or embedded in the clothing for
applications in health care, sports, entertainment,
military, pervasive computing and many other
areas [5]. The nodes in a BAN can be implanted
medical devices, sensors such as ECG electrodes,
activity sensors, data storage etc [9].
Low-power integrated circuits, ultra-low-power RF
technology, wireless communications, and energy
harvesting and storage have gone through many
technological advances which has enabled the
design of lightweight, low-cost, tiny, and
intelligent medical devices, sensors and networking
platforms. With these achievements the concept of
pervasive wireless networks seems to become a
reality in near future [6].
The recent bang of BANs took years of research
and progress in the field of wireless sensor
networks (WSNs), although, the technologies as
well as the development of BANs can be mapped
back to several decades. Plenty of tiny yet powerful
sensor platforms have been demonstrated for
various ubiquitous applications in the past decade.
A BAN is also a type of wireless sensor network,
but it specifically deals with the challenges
associated with monitoring of human body as well
as the interaction of human body with
environments. These challenges are exceptional
because of human body’s complex internal
atmosphere and the individual attributes of human
body that respond to and interact with the outside
world [5].
There are different classifications for BANs based
on whether the devices supported by BANs are
invasive or noninvasive. Invasive wireless body
area networks support in-body communication and
the two-way communication between entrenched
medical devices and the external base stations,
while noninvasive wireless body area networks
support communication among other noninvasive
sensors on or close to the human body and the
surroundings [8].
In this paper, an outlook or survey on applications
and design issues of body area sensor networks is
presented. The rest of the paper is organized as
follows. Section 2 describes the system architecture
of BANs. Applications areas are discussed in
section 3, while section 4 covers the key research
challenges associated with BANs. Section 5
contains overview of candidate wireless
technologies for BANs. In section 6, some practical
issues and relations between different requirements
of BANs are discussed and Section 8 addresses the
issue of positioning of a BAN user. In the end, a
conclusion of all the discussion is presented.
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
20
2. System Architecture /Network
Topologies
In [2], Mark et al have discussed system
architecture and network topologies associated with
BANs. BANs can be organized into different
network topologies based on the application design
choice. Most common network topologies include;
Point-to-point network, where two devices are
connected directly; Star network, where all devices
are connected to a central node or a master node
and communication between two slave nodes
requires passing all packets through the master
node; Mesh network, where any pair of devices can
communicate with each other directly as long as
they are within each other’s radio range; Star-mesh
hybrid network, where a mixed star and mesh
network provides the advantage of simplicity of a
star topology and the flexibility of a mesh
topology; and Cluster tree network, where the mesh
topology is organized to provide a single path
between two devices to reduce the routing
complexity.
Each topology presents its specific set of
advantages and drawbacks regarding network
characteristics such as latency, robustness,
capacity, and the complexity of data routing,
processing, and power consumption. Depending on
the application scenario, BANs with different
topologies are employed either in a standalone
context or in combination of mobile devices (e.g.,
mobile phones) or ambient sensor networks [2].
A stand-alone body area network consists of small
wireless nodes in, on, or in the immediate
neighborhood of the subject. Internet Connected
BANs is a situation where a stand-alone BAN is
connected to the Internet by means of a mobile
base station. The base station acts as a connection
between the BAN subject and the Internet service
provider. The BAN observes, gathers, and stores
data. Collected raw data or locally processed data
can be forwarded via the base station and the
Internet to the service providers (e.g., healthcare
providers, personal trainers, etc.) in real-time if
necessary. The base station server acts not only as
an intermediary between different communication
technologies but also as the protocol gateway
between the BAN, the Internet, and the service
providers [2].
A futuristic scenario is a world with imperceptible
pervasive sensing throughout the environments in
which people live and interact with it. The
architecture of this system will be such that people
are transparently absorbed in the system where
BANs are incorporated like a dream with the global
environments. Subjects of BANs travel within this
pervasive sensing environment to obtain a variety
of services e.g., medical, entertainment, etc.
Handoffs due to mobility are also transparent. The
large amount of data collected through the
pervasive sensing can also be utilized for
knowledge discovery through data mining, pattern
recognition, and machine learning [2].
3. Application Areas
In [2, 8, and 12], different application areas of
BANs are discussed which are summarized here.
Due to various components of BANs that can be
connected and integrated, body area networks are
supposed to be able to provide various functions in
healthcare, emergency, work, research, lifestyle,
sports, or military.
Healthcare: BANs can be used to connect
various devices including digital spectacles and
hearing aids, and will not be restricted to in-home
patient monitoring but will also involve trauma
care, chronic disease research, pharmaceutical
research, and remote assistance in cases of
accidents where mobile devices can be used to
communicate with the hospital and to send data
from the ambulance to alert the concerned
authorities and to get information about providing
first aid to save victim’s life [2].
BANs allow monitoring of patients’ medical status
by sensing and transmitting measurements such as
blood pressure, heart rate, ECG, respiratory rate,
body temperature, chest sounds, etc. Diagnostic
devices can be used to pervasively monitor a
patient’s physical and biochemical parameters
continuously in any environment. Particularly
speaking, BANs can be mainly important for
diagnosis and treatment of patients with chronic
disease, such as hypertension, and diabetes, etc.
BANs are also beneficial to hospital patients who
receive monitoring at different levels for e.g.,
pervasive monitoring of patients in the hospital no
matter where they are, pervasive in-patient
monitoring through implanted devices that enables
medical staff to predict, diagnose, and start
treatment before the patient reaches to adverse
stage of disease [8].
BANs are also highly beneficial for monitoring and
assistance of elderly people, as more and more
people demand a better quality of life. Eventually,
BANs offer a great potential to build up a
personalized healthcare system where cure may be
provided to the patient at the monitoring level,
detection and diagnosis level [10].
In [10], M. Corchado et al, have presented a
distributed telemonitoring system, aimed at
improving healthcare and assistance to dependent
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
21
people at their homes. The system implements a
service-oriented architecture based platform, which
allows heterogeneous wireless sensor networks to
communicate in a distributed way independent of
time and location restrictions. This approach
provides the system with a higher ability to recover
from errors and a better flexibility to change their
behavior at execution time.
Work and Emergency Services: BANs can
also be used to provide services for first responders
such as an intelligent fire, safety, and rescue
system. Using tiny wireless sensors, the system
monitors the condition and location of firefighters.
The sensors can pass on vital information to an
incident commander, who is coordinating a team
from outside the building.
Lifestyle and Sports: BANs enable new
services and functions for wireless body-centric
networks including wearable entertainment
systems, navigation support in the car or while
walking, museum or city guide, heart rate and
performance monitoring in sports, infant
monitoring etc.
Military: A battle dress uniform integrated with
a BAN may become a wearable electronic network
that connects devices such as life support sensors,
cameras, RF and personal PDAs, health monitoring
GPS, and transports data to and from the soldier’s
wearable computer. As a result, BANs provide new
opportunities for battlefield lethality and
survivability.
It is envisioned that wireless body area networks
will become a key component of the future Internet
and serve as an vital vehicle for information access
and exchange in supporting better healthcare,
education, and lifestyle.
4. Research Challenges
In [1, 8, and 12] different challenges associated
with BANs are presented. BAN brings forward a
number of research issues that need to be
considered in the design of radio frequency (RF)
wireless systems.
Users carry several BAN devices globally such as
hearing aids etc; hence, BAN radio is required to
operate worldwide. There is abundance of high
power technologies in ISM bands and they have
cast a degradation effect on the low-power BAN
devices which thus makes them less appealing for
high fidelity medical applications. WMTS bands
are heavily used but their use is restricted to
healthcare facilities in the United States. UWB can
be exploited for wearable applications but it raises
the issue of coexistence with high-data-rate
multimedia applications [12]. The rules for
MedRadio wing band are very strict and limiting.
These issues have provoked the FCC to think about
opening up 2360–2400 MHz range for medical
BANs. This is planned to hold up wideband
entrenched micro-stimulator devices that can serve
as an artificial nervous system to reinstate
sensation, mobility, and function to paralyzed limbs
and organs [1].
Another issue is regarding the channel model.
Channel model plays a vital role in the design of
PHY technologies. Experimental channel modeling
for embedded and wearable devices is hard because
humans and healthcare facilities are involved and
both are governed by regulations.
Antenna design for body area networks is yet
another challenging issue due to limitations on the
size, stuff, and form of the antenna [3]. Only non-
caustic and biocompatible material such as
platinum or titanium can be used for implants,
which results in poorer performance when
compared to a copper antenna. Organ and location
of antenna decides its shape and size which further
restricts the choice of designer [1].
Physical layer protocol design requires reducing
power consumption without affecting reliability.
Flawless connectivity should be maintained in
dynamic environments with the slightest possible
performance degradation in terms of data loss,
throughput, and latency. Rapid turnaround time
from transmit to receive and speedy wakeup from
sleep mode can add significance to power savings
[8].
Energy efficient hardware is also an issue; existing
wireless technologies draw relatively high peak
current and mainly rely on duty cycling the radio
between sleep and active modes to minimize the
average current drawn. Researchers are exploring
several promising techniques such as low-power
listening and wake-up radios, which are intended to
minimize power consumed by idle listening.
BANs are meant to support medical applications
mainly. Hence, safety, security, QoS, and reliability
are important factors besides energy efficiency.
Coexistence of multiple BANs in crowded places
such as hospitals needs a robust MAC protocol.
Efficient duty cycling methods need to be
developed to minimize power consumption. The
MAC protocol should be able to cope with
topology changes caused by movement of nodes.
Channel migration protocols need to be developed
to be able to migrate to a quiet channel when
serious hindrance is noticed. A simple network
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
22
setup process is vital for the ease of amateur users
[8].
In [3], Omeni et al, have presented energy efficient
medium access protocol for wireless medical body
area sensor networks. Using single-hop
communication and centrally controlled
sleep/wakeup times leads to considerable energy
reductions for this application compared to more
flexible network MAC protocols such as 802.11 or
Zigbee. The general power utilization reaches the
standby power as duty cycle is reduced. The
protocol is implemented in hardware as part of the
Sensium™ system-on-chip WBASNASIC, in a
0.13- Mcmos process.
Privacy, confidentiality, authentication,
authorization, and integrity are fundamental
requirements. Traditional security and privacy
techniques are not appropriate for BANs due to
bounded processing power, memory, and energy,
lack of user interface, unskilled users, and global
roaming. Hence, novel lightweight and resource-
efficient methods have to be developed for BANs
[1]. Global roaming over heterogeneous
infrastructure networks further complicates the
end-to-end security provisions.
Medical devices are subject to strict regulations to
promote the safety and welfare of users.
Compliance to applicable regulations set forth by
the FCC, U.S. Food and Drug Administration
(FDA), European Telecommunications Standards
Institute (ETSI), and other regulatory agencies is
essential [1].
5. Candidate Wireless Technologies
In this section, various wireless technologies that
are leading competitors in the upcoming market of
BANs are discussed. End-to-end performance is
determined by the complete protocol stack (i.e.,
including PHY and upper protocol layers).
Bluetooth classic: Bluetooth is a short range
wireless communication standard that defines the
link and application layers to support data and
voice applications. Up to eight Bluetooth devices
form a shortrange network called a piconet.
Bluetooth SIG has developed the Bluetooth Health
Device Profile (HDP) that defines the requirements
for qualified Bluetooth healthcare and fitness
device implementations [1].
Bluetooth low energy: Bluetooth Low Energy
(BTLE) is an upcoming standard that provides
ultra-low-power idle mode operation, simple device
discovery, and reliable point-to-multipoint data
transfer with power save and encryption
functionalities. The key advantages of BTLE are
the strength of the Bluetooth brand and the promise
of interoperability with Bluetooth radios in mobile
phones [1].
ZigBee: ZigBee defines a network, security, and
application layer protocol suite on top of the PHY
and MAC layers defined by the IEEE 802.15.4
WPAN standard. The PHY exploits the direct
sequence spread spectrum technique for
interference tolerance and MAC exploits carrier
sense multiple access with collision avoidance
(CSMA/CA) for channel access. Zigbee provides
full support for IEEE 11073 devices including
glucometers, pulse oximeters, electro-cardiographs,
weight scales, thermometers, blood pressure
monitors, and respirometers[12].
ANT: ANT is a proprietary technology designed
for general-purpose wireless sensor network
applications. ANT features simple design, low
latency, the ability to trade off data rate against
power consumption, and a net data rate of 20 kb/s
(over-the-air data rate is 1 Mb/s)[12].
Sensium: Sensium is a proprietary ultra-low-
power transceiver platform custom designed for
healthcare and lifestyle management applications.
The network adopts a master-slave architecture,
joining a network is centrally managed, and all
communications are single- hop[12].
Zarlink: Zarlink has developed an ultra-low-
power RF transceiver, ZL70101, for medical
implantable applications. It uses a Reed- Solomon
coding scheme together with cyclic redundancy
check (CRC) error detection to achieve an
extremely reliable link. The key features of Zarlink
ZL70101 are extremely low power consumption,
ultralow- power wakeup circuit, and MedRadio
compliance [12].
Other technologies: Proprietary RF
technologies such as BodyLAN and Z-Wave are
also emerging on the horizon. Inductive coupling
(IC) and body coupled communications (BCC)
technologies are also promising. The data rate of IC
is limited, and it cannot initiate communication
from inside the body. BCC transceivers are
capacitively coupled to the skin and use the human
body as a channel to exchange data. BCC is energy
efficient, and alleviates interference and
coexistence issues. BCC can also be used for user
identification and automatic formation of BANs
[1].
6. Challenging Practical Issues
Int. Jour. of Latest Trends in Netw. & Comm Vol-1 No. 1 June 2011
23
BANs face several important challenging issues,
most of which arise from efficiency and practicality
aspects. These issues constrain the solution space,
and need to be considered carefully when designing
mechanisms for data security and privacy in
WBANs.
Conflict between security and efficiency: High efficiency is strongly demanded for data
security in WBANs, not only because of the
resource constraints, but also for the applications.
Wearable sensors are often extremely small and
have insufficient power supplies, which render
them inferior in computation and storage
capabilities. Thus, the cryptographic primitives
used by the sensor nodes should be as lightweight
as possible, in terms of both fast computation and
low storage overhead.
Conflict between security and safety: Whether the data can be accessed whenever needed
could be a matter of patients’ safety. Too strict and
inflexible data access control may prevent the
medical information being accessed in time by
legitimate medical staff, especially in emergency
scenarios where the patient may be unconscious
and unable to respond. On the other hand, a loose
access control scheme opens back doors to
malicious attackers. It is hard to ensure strong data
security and privacy while allowing flexible access.
Conflict between security and usability:
The devices should be easy to use and foolproof,
since their operators might be non-expert patients.
As the setup and control process of the data
security mechanisms are patient-related, they shall
involve few and intuitive human interactions. For
instance, to bootstrap initial secure communication
between all the nodes in a WBAN for secure data
communication, device pairing techniques can be
adopted. Increasing usability by omitting some
manual steps may not be good for security.
Requirement for device
interoperability: Patients may buy sensor
nodes from different manufacturers, among which
it is difficult to pre-share any cryptographic
materials. It is difficult to establish data security
mechanisms that require the least common settings
and efforts, and work with a wide range of devices.
7. Positioning of WBAN User
Positioning of a WBAN user in critical condition is
an important issue in WBAN. A patient equipped
with WBAN sensors can get stuck into any
critical condition anywhere so it is important to
monitor them continuously. There are different
technologies for localization, but their stickiness
with certain application does not make them
unanimous. In WBAN a technology is needed
which can serve two way communication as well as
positioning of the user. Since GSM technology is
dispersed worldwide with huge infrastructure so
GSM is better option than others, because of the
two way communication and positioning we can
rely upon single entity [7].
8. Conclusion
The WBAN is an emerging and promising
technology that will change people’s healthcare and
daily life experiences revolutionarily. Data
security, safety, efficiency and privacy in WBANs
is an important area, and there still remain a
number of considerable challenges to overcome.
The research in this area is still in its infancy now,
but it is believed it will draw an enormous amount
of interest in coming years. This paper has
highlighted many research and practical issues
related to BANs. Addressing all these challenges is
most likely to require new approaches to media
access and protocol design. Engineers, researchers,
and practitioners from multiple disciplines, must
come together and strive hard to overcome
technical roadblocks in order to bring the vision of
a ubiquitous body area network to reality.
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