Enhancing Cyber Security in Power Substation using RSA Algorithm … · 2018-06-17 · Enhancing...

Enhancing Cyber Security in PowerSubstation using RSA Algorithm and

LSB Stegnography Methodology

PRABHAKARAN RAssistant Professor (SR)

Department of Computer Science and EngineeringVIT University, Chennai Campus, Chennai 600127

Tamil Nadu, IndiaEmail id: [email protected]

Dr.S.AshaAssociate Professor

Department of Computer Science and EngineeringVIT University, Chennai Campus, Chennai 600127

Tamil Nadu, IndiaEmail id: [email protected]

May 24, 2018

Abstract

Stegnography means covered writing. Art and Scienceof hiding information in ways that prevent detection. Itcan be used on audio, text, packet headers, or images .Similar to Cryptography Cryptography: scrambles messageSteganography: hides message

In this project entitled Enhancing Cyber Security inPower Substation using RSA Algorithm and LSB Stegnog-raphy Methodology, I have focused on least significant bitmodification techniques of spatial domain. I have analyzedand compared the variants of this algorithm in terms of

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International Journal of Pure and Applied MathematicsVolume 118 No. 24 2018ISSN: 1314-3395 (on-line version)url: http://www.acadpubl.eu/hub/Special Issue http://www.acadpubl.eu/hub/

effectiveness and hiding capacity. Effectiveness of the algo-rithm is measured by user evaluations determining at whichpoint alteration to the images became apparent.

1. 1 bit, 2 bits, 3 bits and 4 bits LSB (hiding as well asextraction)

2. 24 bits plane (Red, Green, Blue) and 32 bits plane(Red, Green, Blue, Alpha) BPCS

3. Bitwise XOR Implementation between LSB and pay-load

4. Steganography Based on File Format

1 Introduction

Steganography is the art and science of communicating in a waywhich hides the existence of the communication. In contrast toCryptography, where the enemy is allowed to detect, intercept andmodify messages without being able to violate certain security premisesguaranteed by the cover message with the embedded cryptosystem.The goal of Steganography is to hide messages inside other harmlessmessages in a way that does not allow any enemy to even detectthat there is a second message present. In image steganography theinformation is hidden exclusively in images.

RSA algorithm is asymmetric cryptography algorithm. Asym-metric actually means that it works on two different keys i.e. PublicKey and Private Key. As the name describes that the Public Keyis given to everyone and Private key is kept private.The idea ofRSA is based on the fact that it is difficult to factorize a large in-teger. The public key consists of two numbers where one numberis multiplication of two large prime numbers. And private key isalso derived from the same two prime numbers. So if somebodycan factorize the large number, the private key is compromised.Therefore encryption strength totally lies on the key size and if wedouble or triple the key size, the strength of encryption increasesexponentially.

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International Journal of Pure and Applied Mathematics Special Issue

2 RELATED WORK

2015: G. Prashanti and K. Sandhyarani have done survey on recentachievements of LSB based image steganography. In this surveyauthors discuss the improvements that enhance the steganographicresults such as high robustness, high embedding capacity and un-detectability of hidden information. Along with this survey two newtechniques are also proposed. First technique is used to embed dataor secret messages into the cover image and in the second techniquea secret gray scale image is embedded into another gray scale image.These techniques use four state table that produce pseudo randomnumbers. This is used for embedding the secret information. Thesetwo methods have greater security because secret information ishidden on random selected locations of LSBs of the image with thehelp of pseudo random numbers generated by the table.

2014-2015: Savita Goel proposed a new method of embeddingsecret messages in cover image using LSB method using differentprogressions. Authors compare the quality of stego image with re-spect to cover image using number of image quality parameters suchas Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE),histograms and CPU time, Structure Similarity (SSIM) index andFeature Similarity Index Measure (FSIM). Their study and experi-mental results shows that their proposed method is fast and highlyefficient as compared to basic LSB methods.

2015: Bingwen Feng, Wei Lu, and Wei Sun in their paper Se-cure Binary Image Steganography Based on Minimizing the Dis-tortion on the Texture purposed a state of-the-art approach of bi-nary image steganography. This technique is proposed to minimizethe distortion on the texture. In this method of steganographyfirstly the rotation, complement and mirroring invariant texturepatterns are extracted from the binary image. They also proposeda measurement and based on this proposed measurement this ap-proach is practically implemented. Practical results show that pro-posed steganographic approach has high statistical security withhigh stego image quality and high embedding capacity.

2014: On the based on Huffman Coding, Amitava Nag presenta novel steganographic technique of LSB substitution. Their tech-nique basically focuses on high security, larger embedding capacityand acceptable level of stego image quality. Firstly Huffman tree

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is produced to encode every 8 bits of secret image. After encod-ing, they divide the encoded bits into four parts and have 0 to 3decimal values. Location of embedding a message in cover image isdetermined by these decimal values. 2012: In this author proposesan enhanced LSB algorithm for image steganography. In this pro-posed work they only embed secret information in blue componentof the RGB colour space. In their technique first MN size coverimage is selected. After selection of cover image only blue compo-nent is used for embedding secret information. They also make useof pixel filters to access the best regions to embed information incover image to obtain 5 best possible rate. Experimental resultsshow that this technique reduces the distortion level of cover imageand stego image has very good visible quality and changes in coverimage are negligent to Human Visual System (HVS). This methodreduces the leap in colour scale because only blue components areused to embed the secret information.

2010: On the bases of Human visual system (HVS) X. Qingproposed a new technique in which sensitive information is embed-ded in all planes of RGB components of an image. In this techniquemultiple plan-bit is used with adaptive nature of information hid-ing algorithm. This proposed method has high embedding capacitythan traditional LSB method and low computational complexity.Proposed system also has good quality of stego image.

2009: H. Yang presented a new adaptive LSB based methodfor image steganography. It uses the pixel adjustment techniquefor better stego image quality. This adaptive LSB substitutionresults in high hidden capacity. LSB based image steganographymethod is proposed. To hide the data common bit pattern is used.According to the message and the pattern bits LSBs of pixels aremodified. This method has low hidden capacity.

3 PROPOSED ALGORITHM

3.1 LSB

Least Significant Bit (LSB) is the bit position in a binary integergiving the units value, that is, determining whether the number iseven or odd. The LSB is sometimes referred to as the right-mostbit, due to the convention in positional notation of writing less

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significant digits further to the right. It is analogous to the leastsignificant digit of a decimal integer, which is the digit in the ones(right-most) position. In digital steganography, sensitive messagesmay be concealed by manipulating and storing information in theleast significant bits of an image or a sound file. In the context ofan image, if a user were to manipulate the last two bits of a colorin a pixel, the value of the color would change at most +/- 3 valueplaces, which is likely to be indistinguishable by the human eye.The user may later recover this information by extracting the leastsignificant bits of the manipulated pixels to recover the originalmessage.

3.2 BIT PLANE

A bit plane of a digital discrete signal (such as image or sound) is aset of bits corresponding to a given bit position in each of the binarynumbers representing the signal. It is possible to see that the firstbit plane gives the roughest but the most critical approximation ofvalues of a medium, and the higher the number of the bit plane,the less is its contribution to the final stage. Thus, adding a bitplane gives a better approximation. Bitplane is sometimes usedas synonymous to Bitmap; however, technically the former refersto the location of the data in memory and the latter to the dataitself.[2] One aspect of using bit-planes is determining whether abit-plane is random noise or contains significant information. Onemethod for calculating this is compare each pixel (X,Y) to threeadjacent pixels (X-1,Y), (X,Y-1) and (X-1,Y-1). If the pixel is thesame as at least two of the three adjacent pixels, it is not noise. Anoisy bit-plane will have 49% to 51% pixels that are noise

Figure 1 Bit Plane

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3.3 SPIRAL EMBEDDING

Spiral embedding is a simple strategy to implement steganography.Like all steganographic methods, it embeds the data into the coverso that it cannot be detected by a casual observer. The techniqueworks by replacing some of the information in a given pixel withinformation from the data in the image. While it is possible toembed data into an image on any bit-plane, LSB embedding is per-formed on the least significant bit(s). This minimizes the variationin colors that the embedding creates. For example, embedding intothe least significant bit changes the color value by one. Embeddinginto the second bit-plane can change the color value by 2. If embed-ding is performed on the least significant two pixels, the result isthat a color in the cover can be any of four colors after embedding.Steganography avoids introducing as much variation as possible,to minimize the likelihood of detection. In a LSB embedding, wealways lose some information from the cover image

Figure 2 The Spiral Embedding pattern. The height informationis embedded into the blue line pixels, the width information into

the red pixels, and the message into the green pixels.

3.4 ALTERING THRESHOLD

Thresholding is the simplest method of image segmentation. Froma grayscale image, thresholding can be used to create binary images.The simplest thresholding methods replace each pixel in an imagewith a black pixel if the image intensity is less than some fixedconstant T or a white pixel if the image intensity is greater thanthat constant.

3.5 APPENDED DATA

A simple and common steganography technique is to append dataat the end of image file. This technique works because most image

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viewers ignore any appended data and hence a stego message re-mains hidden. Linux cat command can be used for appending dataat the end of image file.

3.6 PNG CHUNK ANALYSIS

Chunk Analysis is a network-byte-order CRC-32 computed overthe chunk type and chunk data, but not the length.Chunk typesare given a four-letter case sensitive ASCII type/name; compareFourCC. The case of the different letters in the name (bit 5 ofthe numeric value of the character) is a bit field that provides thedecoder with some information on the nature of chunks it does notrecognize. The case of the first letter indicates whether the chunk iscritical or not. If the first letter is uppercase, the chunk is critical;if not, the chunk is ancillary. Critical chunks contain informationthat is necessary to read the file. If a decoder encounters a criticalchunk it does not recognize, it must abort reading the file or supplythe user with an appropriate warning. The case of the second letterindicates whether the chunk is ”public” (either in the specificationor the registry of special-purpose public chunks) or ”private” (notstandardised). Uppercase is public and lowercase is private.

3.7 CHANGING COLOUR MAP

When an image is encoded in this way, color information is notdirectly carried by the image pixel data, but is stored in a separatepiece of data called a palette: an array of color elements. Everyelement in the array represents a color, indexed by its positionwithin the array. The individual entries are sometimes known ascolor registers. The image pixels do not contain the full specificationof its color, but only its index in the palette. This technique issometimes referred as pseudocolor or indirect color, as colors areaddressed indirectly. This technique can be exploited to hide datain image using suitable palette or colour map. To decode data wemust try different random colour maps.

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4 SCREENSHOTS

Figure 3 Opening an image to analyse

Figure 4 Hidden Image found in 0th bit plane

Figure 5 Changing color map

Figure 6 Hide Image GUI

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Figure 7 Hidden data visible on altering threshold

Figure 8 Hide Text using LSB

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Figure 9 Hide Image inside bit plane of cover image

Figure 10 Extracting metadata from image

Figure 11 PNG Chunk Analysis

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4.1 FLOW CHART

Figure 12 Flow Chart

4.2 LIMITATIONS

1. All the steganography methods are of spatial domain i.e. di-rectly modified image pixels.

2. Appended data extraction does not work for JPEG images.

3. Tool does not provide options for compression or encryptionof payload.

4. JPEG images cannot be used as cover image to hide data.

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5 RESULTS AND DISCUSSION

5.1 Comparing hiding image in different bit planes

Figure 13 Cover Image for hiding secret image bit plane

Figure 14 Secret image hidden in 0th bi plane

Figure 15 Secret image hidden in 1st bit plane

Figure 16 Secret image hidden in 2nd bit plane

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Figure 17 Secret image hidden in 3rd bit plane

Figure 18 Original secret image

5.2 Analyzing different bit planes for any hid-den image

Figure 19 Original RGB colour image

Figure 20 7th bit plane

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Figure 23 2nd bit plane

Figure 24 Hidden image in 0th bit plane

5.3 Changing colour map of indexed image tosee any hidden data

Figure 25 Original Indexed image

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Figure 26 Colour Map

Figure 27 Colour Map 2

Figure 28 Colour Map 3

5.4 Hiding Text in different bits

Figure 29 Original 24 bit PNG image

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Figure 30 Data hidden in 0th bit

Figure 31 Data hidden in 0th and 1st bits

Figure 32 Data hidden in 3rd and 4th bits


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6 CONCLUSION

Image-Stegano tool can be used by individuals/ organization. Thistool is platform independent and is handy for analyzing commonsteganography methods. Though there are several others steganog-raphy tools available but Image-Stegano can be said as combinationof many tools and since it is open source so new functionalities willbe added over time by volunteer contributors. Besides functionalrequirements, we have also focused on non-functional requirements(Nice UI and UX, Efficient). The tool has limitation that it doesnot accept jpeg images as carrier image to hide data. Also this tooldoes not use compression and encryption of payload.

References

[1] . Saha and S. Sharma, Steganographic Techniques of Data Hid-ing using Digital Images, in Defence Science Journal, vol. 62,no. 1, 2012 January, pp. 11-18.

[2] ilman, J., Steganography and Steganalysis: An Overview,SANS Institute, 2001.

[3] amil, T., Steganography: The art of hiding information in plainsight, IEEE Potentials, 18:01, 1999.

[4] ohnson, N.F. Jajodia, S., Exploring Steganography: Seeingthe Unseen, Computer Journal, February 1998.

[5] ei-ichiro Kamata, et al: Depth-First Coding for Multi-ValuedPictures Using Bit-Plane Decomposition, IEEE Trans. on CT,Vol.43, No.5, pp.1961-1969, May, 1995.

[6] ttps://www.w3.org/TR/PNG-Chunks.html

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