Pritheega d/o Magalingam...Razak Faculty of Technology and Informatics Level 7, Menara Razak,...

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Teaching Portfolio

Pritheega d/o Magalingam Ph.D. (Mathematical Sciences)

M.Sc. (Information Security) B.Sc. (Computer)

Senior Lecturer

Advanced Informatics Department Razak Faculty of Technology and Informatics

Level 7, Menara Razak, Universiti Teknologi Malaysia,

Jalan Sultan Yahya Petra, 54100 Kuala Lumpur.

Office: +603-2203 1442

Primary email: [email protected]| Secondary email: [email protected]

Nationality: Malaysian

CORRESPONDING ADDRESS : Advanced Informatics Department Razak Faculty of Technology and Informatics Level 7, Menara Razak,

Universiti Teknologi Malaysia, Jalan Sultan Yahya Petra, 54100 Kuala Lumpur.

Tel: 03-22031442 (O) 0167225320 (HP)

E-mail: [email protected]

Website: https://www.linkedin.com/in/pritheega-magalingam

mailto:[email protected]

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Contents

ACADEMIC QUALIFICATION ..................................................................................................................... 3

TEACHING GOALS .................................................................................................................................... 4

PERSONAL PHILOSOPHY ......................................................................................................................... 4

PRACTICES OF ASSESSMENT ................................................................................................................. 5

EFFORTS TO IMPROVE TEACHING .......................................................................................................... 6

TEACHING EXPERIENCES/ RESPONSIBILITIES ........................................................................................... 7

POSTGRADUATE SUPERVISION ................................................................................................................. 7

AWARDS AND HONORS RECEIVED ......................................................................................................... 8

SHORT TERM GOALS ............................................................................................................................... 9

Appendix I – A Sample of Course Outline Handout Appendix II– A Sample of Course Assignment Appendix III - List of attended seminar, conferences, workshops and courses

Appendix IV - Some students’ comments and feedbacks

Appendix V – Award Received

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ACADEMIC QUALIFICATION

Year 2015 : Ph.D. (Mathematical Sciences)

Major: Information Security

Universiti: Royal Melbourne Institute of Technology University

(RMIT University), Melbourne, Australia.

Duration: 27th February 2012-16th July 2015

Year 2008 : Master in Computer Science (Information Security)

Universiti: Centre for Advanced Software Engineering (CASE)

University Technology Malaysia, International Campus, Kuala Lumpur

Grade: First Class Honours

Duration : July 2007 – November 2008

Year 2005 : Bachelor of Science(Computer)

Major:Software Engineering

Universiti: Faculty of Computer Science and Information System, University

Techology, Malaysia, Skudai

Grade: Second Class Honours (Upper Division)

Duration: June 2001- November 2005

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TEACHING GOALS

Encourages and values high expectations of students’ learning. I encourage lecturer-student contact in and out of classes. I give motivation and improve students' involvement in learning. I believe that my concern helps students to get through rough times and keep on working. Some strategies that I use are:

• Share past experience, values and attitudes.

• Design projects that bring students to my office and discuss in groups.

• Treat students as human beings: ask how they are doing.

• Use email and WhatsApp regularly to encourage them to finish their work and inform

them.

• Create a forum and ask students to give constructive feedback on each other’s work

and to explain ideas

• Encourage teamwork and leadership among students

• User group discussion, collaborative projects, case study analysis and group

presentations to improve students’ communication skill and braveness to present in

public.

• Use technology to encourage active learning; students can have forum discussion

from anywhere outside the classroom.

• Use e-learning to improve model of asking questions, accepting and giving feedback

to their friends’ comments.

• Encourage punctuality through online assignment submission.

PERSONAL PHILOSOPHY

Clearly indicate my own Personal philosophy towards student learning with strategies for continuous improvement. I believe that teaching is not just about delivering the course contents but also to promote meaningful learning and lifelong learning to the students. My role as a lecturer is to monitor how students are adapting well in the class by asking them questions about a specific topic being taught in class and to help them repair misunderstandings. Speaking and writing clearly and concisely is essential. I often use diagrams and demonstrations to explain and let them go through with me some exercise to ensure they fully understand the topics being taught. I always help students to apply critical analysis while doing assignment and projects and be the driving forces behind new, appropriate technology. I encourage students to do research on the topic that they are comfortable but related to my subject. This way students will be able to explore where to apply what they have learnt in class. Based on their interest they find problems related to the area of research and suggest to apply metrics and measures taught in class to find solutions. This way, students are not controlled or dominated to choose a particular area of lecturer’ interest but I give them the freedom to choose. I let them do mini-presentation so that they don’t run out of topic. I find that students are more engaged when we are performing problem-solving than when they are simply listening to a lecture. There is a certain joy experienced by solving a challenging problem. This interactive approach to teaching allows students to feel that reward.

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Through this philosophy, I teach in the awareness that the students need the opportunity to develop themselves rather than being spoon-fed by the lecturer. The rapport between student and lecturer should be encouraged and improved constantly. With good rapport, the students can have a more comfortable discussion inside or outside of class. On top of that, I feel very strongly that to be an effective lecturer, I need to treat individual students with respect. I must attempt to get to know each student by name, and his or her strengths and weaknesses. I must try to accommodate questions at any time, not just during class and office hours. My job is not only to show them what I know, but to teach them what they need to know, and more importantly to facilitate their learning. Finally, I hope to be able to instill in students a love of learning. I hope to teach my students that learning is more than just exams and grades. I hope that the real value in their education is not found in their grade point average or their resume, but in the knowledge that they take away.

PRACTICES OF ASSESSMENT

Constructively align assessment methods, that include both formative and summative assessment, with the intended learning outcomes and the T&L activities. I make sure that the assessment is aligned with the intended learning outcomes. The students are continuously assessed throughout the semester. Mid Term Paper/ Mid Term Test The test is usually given towards the end of the semester. To ensure the questions have a different level of difficulties, I focus on level 1 to 5 of Bloom's taxonomy for the test. The test is a comprehensive evaluation of course which covers all material (basic knowledge) from week 1 to week 14. The test takes 30% of the total course marks. There is no final exam for this subject. Assignments and Project The assignments are divided into two categories; individual and group. The first and second assignment is an individual assignment. The assignments are usually involving the use of computer software. I want to make sure all the students know how to use the software and assignments are given separately for each individual. The students will be given about 2 to 3 weeks to complete their assignments. Each assignment is given one after another and not together. This is to avoid students to feel brain drain or tired. Evaluating students on each software that has been taught in class is important to estimate the level of understanding and usage of the software. This is also another way to evaluate students’ readiness to contribute their knowledge in the group project. The following assessment is through a a group project. Students are given time to explore their own scenario based on a research study and propose solutions. A class presentation will be held for their group project. The students will be given about 4 weeks to complete their project.

Class Active Learning (Forums), Workshop (Hands-on) During the class lecture session, 2-3 class activities are conducted through elearning to evaluate students’ knowledge on the application of metrics and measures taught in class on the real-world case study. Also, it is conducted as a preparation for the class project. Workshops are being held based on the number of software being taught in the class. Based on the class activity, workshops and the overall performance of the students in the class, I will give marks for observation and self-reflection.

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EFFORTS TO IMPROVE TEACHING

Clearly provides self-reflection of teaching development and relates it to CQI of teaching strategies. I constantly ask questions to myself to improve my teaching strategy and performance over time and follows some of these methods to improve my teaching: After each lesson, I jot down a few notes describing the reaction and feelings of students towards my lecture and activities given. There are some questions I ask myself:

• Was the lesson too easy or too difficult for the students? • Did the students understand what was being taught? • What problems arose?

Apart from that, I do give importance to students’ feedback. End of every class, I will verbally ask students how they feel about the lesson and teaching. I will ask students to fill up the lecturers’ online evaluation form (e-PPP) and also send their feedback through email.

Ongoing teaching improvements are made by getting these questions answered:

• Were students on task? • With what parts of the lesson did the students seem most engaged? • With what parts of the lesson did students seem least engaged with? • How effective was the overall lesson? • How can I do it better next time? • Did I meet all of my objectives? • How did I deal with any problems that came up during instruction? • Was I perceptive and sensitive to each of my students’ needs? • How was my overall attitude and delivery throughout the class?

These questions are important and I analyse it during and end of each lesson. I will make appropriate changes wherever needed.

Besides that, I will do more research and reading journals that help to update with current issues on new technologies, teaching and learning. Thus, generates new ideas during classes.

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TEACHING EXPERIENCES/ RESPONSIBILITIES

POSTGRADUATE TAUGHT COURSE TEACHING (2010-2019)

MSc In Computer Science (Information Security)

MCS 1493 : Law, Investigation and Ethics

Master of Science (Information Assurance)

MANA 1563 : E-crime Investigation and Incident Response Management

MANA 1533 : Enterprise Information Assurance

MANA 2133 : Business Continuity Management

Master of Science (Business Intelligence and Analytics)

MANB2163 : Social Network Analytics

Doctor of Software Engineering

EANE 2113 : Software Engineering Research Paradigm

POSTGRADUATE SUPERVISION

PhD:

Main-Supervisor

• Inthrani Shamugam: Information Security Risk Assesment Framework for Data Centers in Malaysian Public Sector.

• Chai Ling: High Risk Customer Profiling in Banking Industry with Big Data Analytics

• Khaled Gubran: Identifying Suspicious Behaviour in Bitcoin Network using Unsupervised Approach.

• Surenthiran Krishnan: A Framework for Heart Disease Predictive Analytics

• Owolewa Rasheed Olabisi: Adaptive Identity Access Management (AIAM) Model For Public Cloud Computing In Banking Environment.

Masters:

Main Supervisor

• (2018-2019) Yalini Bavan: Predicting unsafe food from amazon user reviews using machine learning.

• (2018-2019) Komathi Krishnan: An Enhanced IoT Security Architecture Layers For The Healthcare Service

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• (2018-2019) Hasif Bin Zulkifli: Application Of Multi-Layer Perceptron Neural Network Algorithm To Predict The Trend Of Eurusd Market

• (2018-2019) Chua Kean Hoe: Digital Crime Evidence Acquisition for Social Media Applications on Windows 10 System

• (2018-2019) Najmi Azfar Bin Mohd Rosli: A Practical Approach Of Cyber Threat Hunting Framework For Government Agency

• (2018-2019) Mohd Hafzi Bin Marzuki: A Proposed Digital Forensics Framework To Support E-Crime Investigations In Malaysian Armed Forces.

• (2016- 2017) Sharmiladevi Sonah Kakian@Rajoo: False Report Identification Algorithm using Text Classification Technique for CitiAct Application.

• (2016-2017) Fatimah Binti Mohamad Yunus: Data Quality Evaluation Model for Transportation Agency.

AWARDS AND HONORS RECEIVED

Awards/Achievements:

1) Awarded for Active Blended Learning Course Year/Sem: Semester 2 2015/2016,

Semester 1 2016/2017, Semester 1 2017/2018

(Subject: Enterprise Information Assurance)

Year/Sem: Semester 2 2016/2017

(Subject: Business Continuity Management)


(Subject: ECrime Investigation and Incident

Response Mgt, Social Network Analytics)



Response Mgt)



Response Mgt, Social Network Analytics)

2) Anugerah Perkhidmatan Cemerlang From Advanced Informatics School, UTM KL(2018)

3) Anugerah Penulis dalam Journal Berindex Faculty Level (2018), Received in 2019

4) Train the Trainer HRDF (2017)

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SHORT TERM GOALS

My short term goals will be to update my learning modules. I will also want to improve my rapport

with my students. I believe a good rapport help to produce good teaching. My aim is to continously

increase research activities in the area of teaching and learning.

Appendix I – A Sample of Course Outline Handout

COURSE OUTLINE

Department & Faculty: UTM AIS Page : 1 of 4

Course Code: MANA 1563

Course Name: E-crime Investigation And Incident Response Management

Total Contact Hours: 42

Semester: SEM 1 2018/2019 Academic Session: 2017/2018

Prepared by:Dr. Pritheega Magalingam Name: Signature: Date:

Certified by: (Program Coordinator) Name: Signature: Date:

Lecturer : Dr. Pritheega Magalingam

Room No. : 07.40.01 (MJIIT)

Telephone No. : 03-22031442

E-mail : [email protected]

Synopsis

: This course will discuss on how to conduct computer forensic from acquiring digital evidence to reporting their findings. It includes how to set up a forensics lab, how to acquire the necessary tools and how to conduct an investigation and subsequent digital analysis.

LEARNING OUTCOMES By the end of the course, students should be able to:

No. Course Learning Outcome Programme Outcome

Taxonomies (C, P, A)

Weightage (%)

Assessment Methods

CO1

CO2

CO3

CO4

Apply and integrate knowledge concerning e-crime investigation and IRM

Develop computer forensic model and tools using appropriate technique as practiced in forensic investigations.

Manipulate some digital forensic investigation techniques using tools to support impact analysis

Explain the importance of digital forensic process/framework and justify the impact of forensic analysis towards the e-crime incident management

PO1

PO2

PO3

PO5

C5 TS 1-3

C1-6 CTPS1-3

P1-7 CS1-6

A1-4 LL1-2

40

30

10

20

A = 10%, CS = 10%

F=20%

F = 20%, T = 10%,

PR = 10%

CP = 5%, A = 10%,

Pr=5%

(T – Test ; PR – Project ; Q – Quiz; HW – Homework ;

Pr – Presentation;

CP: Class Participation;CS: Case Study; F – Final Exam; PR-

Project Report)


COURSE OUTLINE



Course Name: E-crime Investigation And Incident Response Management Total Contact Hours: 42


STUDENT LEARNING TIME (SLT)

Teaching and Learning Activities Student Learning Time (hours)

1. Face-to-Face Learning

a. Lecturer-Centered Learning

i. Lecture

21

b. Student-Centered Learning (SCL)

i. Laboratory/Tutorial

ii. Student-centered learning activities– Active Learning, Project Based Learning

21

2. Self-Directed Learning

a. Non-face-to-face learningor student-centered learning (SCL) such as manual, assignment, module,etc.

34

b. NALI/MOOCs/e-Learning 15

c. Revision 14

d. Assessment Preparations 10

3. Formal Assessment

a. Continuous Assessment 2

b. Final Exam 3

Total (SLT) 120

TEACHING METHODOLOGY

PO SCHOLARSHIP OF KNOWLEDGE

LEARNING ENVIRONMENT

TEACHING AND LEARNING METHODS

ASSESSMENT METHODS

PO1 Advanced Knowledge

Ability to demonstrate higher order thinking skill and view things in broader perspective

• Involve discussions

• Critic ideas

• Experiential

• Real practices

• Create hypothesis

• Seek opinion from others

• Think scholarly

• Knowledge sharing

• Cooperative learning

• Assignment

• Examination

• Academic Writing

• Case Study

PO2 Research Skills

• Ability to apply appropriate research methodologies, techniques and

• Involve higher order thinking

• Work / Lab setting

• Multi disciplinary knowledge

• Practicality

• Article Critique

• Mini Research/ action research

• Project work

• Simulation

• Seminars/Conferences

• Oral examination (viva)

• Assignment

• Project report

COURSE OUTLINE





tools within the discipline;

• Ability to integrate existing and new ideas into established knowledge

• Ability to integrate existing and new ideas into established knowledge

• Ability to apply knowledge to the immediate discipline within wider community.

• Relevant research areas

• Mentor-mentee researcher

• Dissertation / Theses

• Seminar papers

• Prototype

PO3 Critical Thinking

• Ability to apply knowledge to the immediate discipline within wider community.

• Ability to demonstrate critical thinking and creative problem solving;

• Involve discussions

• Critic ideas

• Think scholarly


• Case study

• Guided Lectures

• Group Discussion

• Problem-based Learning

• Constructivist Approach

• Paper Critique

• Knowledge sharing

• Intellectual discourse

• Assignment

• Examination


• Self-Reflection

• reflective critique

PO5 Communication

• Ability to confidently, effectively and coherently communicate information and knowledge through listening, speaking, visualizing and writing to acceptable standard;

• Ability to acquire, organize, evaluate and present ideas using appropriate technology;

• Ability to demonstrate open-mindedness and receptiveness to new ideas.

• Express ideas in oral and written communication

• Peers involvement

• Present ideas in structured form

• Defend idea

• Tutorial


• Problem Based Learning

• Project based learning

• Case study

• Internships

• Field trips

• Class Participation

• Oral Presentation

• Public Speaking

• Quiz

• Assignment

• Examination

• Presentation


COURSE OUTLINE





WEEKLY SCHEDULE

Week 1 : Computer Forensics and Investigations as a Profession

Week 2 : Nature of Cyber Crime and Understanding Computer Investigations

Week 3-4 : The Investigator’s Office and Laboratory, and Data Acquisition

Week 5-6 : Processing Crime and Incident Scenes Management, and Working

with Windows and DOS Systems

Week 7 : Computer Forensic Tools

Week 8 : Semester Break

Week 9 -10 : Computer ForensicsAnalysis and Validation, Email Investigations

Week 11-12 : Report Writing for Investigations

Week 13-14 : Experts Testimony in Investigations

Week 15 : Class Project Presentation and Examination Review

Week 16 : Study Break

Weak 17 : Final Exam

REFERENCES : REFERENCES:

1. Brown Christopher L.T. Computer Evidence: Collection and Preservation. Thomson Delmer Learning, 2005(ISBN 1584504056).

2. Casey, Eoghan, ed. Digital Evidence and Computer Crime. Academic Press, 2003 (ISBN 0121631044). 3. Prosise, Chris, Kevin Mandia, and Matt Pepe. Incident Response: Computer Forensic.McGraw-Hill, 2003 (ISBN

007222696X). 4. Stephenson, Peter. Investigating Computer-Related Crime. CRC Press, 2000 (ISBN 0-8493-2218-9).

GRADING: (Provide details on the allocation of marks and the time schedule for all quizzes, tests, assignments, etc.)

Assessment Number % each % total

1. Group Project& Presentation

1 20 20

2. Assignment 2 5 10

3. Test 1 15 15

4. Class Participation 1 5 5

5. Case Study 1 10 10

6. Final Exam 1 40 40

Total 100

School: Advanced Informatics School (UTM AIS) Universiti Teknologi Malaysia

Page 1 of 6

CourseCode : MANB 2163 Course Name : Social Network Analytics Contact Hours : 42

Semester : 2 Academic Session : 2018/2019

Lecturer : Dr.Pritheega Magalingam

Room No. : Razak Faculty of Technology and Informatics,

Level 7, Menara Razak, UTM Kuala Lumpur Campus,

Jalan Sultan Yahya Petra,

54100 Kuala Lumpur

Telephone No. : 0167225320


Synopsis :

Social network analysis is the mapping and measuring of relationships and flows between entities. This subject delivers both visual and mathematical analysis of human relationships. We will learn about graphs to understand how to represent social network data. R provides powerful packages to conduct social network analysis. The network analysis packages able to show relationships in a form of graph, helps to handle huge graphs, create and manipulate graphs using various metrics and measures.

LEARNING OUTCOMES

By the end of the course, students should be able to:

STUDENT LEARNING TIME (SLT)

Course Learning Outcomes Programme

Outcome(s)

Taxonomies

(C,P,A)

Assessment

Methods

Weightage

(%)

CO1

Integrate the concepts

and method of web and

text analytics for

processing unstructured

data into structured

format, perform

classification and text

clustering, and analyzing

it to extract information

PO2 P5 TP

R

20

10

and pattern discovery for

organization process

efficiently and effectively.

CO2 Critically evaluate

current issues of

business intelligence and

analytics

PO3 C5

A

Asg

30

CO3 Engage ethical values

when identifying issues in


analytics

PO4 A4

EM1-EM3

Ob

SR

TP

5

5

10

CO4 Demonstrate leadership

skills in the reporting and

presenting issues in


analytics

PO9 A4

LS1-LS2

Pr

PR

10

10

Legend:

PO: Program Outcome A: Affective P: Psychomotor Ob: Observation AP : Academic Publication SR: Self- Reflection LL: Lifelong Learning C: Cognitive CTPS: Critical Thinking and Problem Solving As: Assignment Pr: Presentation F: Final Exam T: Test Q: Quiz PR: Project Report PA: Peer-Assessment SA: Self-Assessment LS : Leadership Skill SP: Seminar Paper CP: Class Participation TP: Term Paper R: Report Asg: Assignment

TEACHING & LEARNING AND ASSESSMENT METHODS

PO SCHOLARSHIP OF

KNOWLEDGE

LEARNING

ENVIRONMENT

TEACHING AND

LEARNING

METHODS

ASSESSMENT

CRITERIA

PO2

• Ability to apply

appropriate research

methodologies,

techniques and tools within the discipline;

• Ability to integrate

existing and new ideas

into established

knowledge

• Ability to integrate

existing and new ideas

into established knowledge


knowledge to the

immediate discipline

• Involve higher

order thinking

• Work / Lab

setting

• Multi

disciplinary knowledge

• Practicality

• Relevant

research areas

• Article Critique

• Mini Research/

action research

• Project work

• Simulation

• Seminars/Confe

rences

• Mentor-mentee

researcher

• Systematic

review

• Research

methods

• Scope of the

research

• Research contribution

within wider community.

PO3


knowledge to the

immediate discipline

within wider

community.

• Ability to demonstrate

critical thinking and creative problem

solving;

• Involve

discussions

• Critic ideas

• Experiential

• Real practices

• Create

hypothesis

• Seek opinion

from others

• Think scholarly

• Cooperative

learning

• Case study

• Guided Lectures

• Group

Discussion

• Problem-based

Learning

• Constructivist

Approach

• Paper Critique

• Knowledge

sharing

• Intellectual

discourse

• Subject

Knowledge

• Pedagogical

Knowledge

• Commitmen

t to Personal

Growth

• Teaching

Effectiveness

• Innovation

and

Disseminati

on

• Quality of

Innovation

PO4

• Possess a profound

respect for truth, professional and

intellectual integrity

and ethics of research

and scholarship;

• Meta-thinking

• Respect for

truth

• Involve personal goal

• Honesty and

integrity for

fulfilling

professional

responsibilities

• Geographical

diversity

• Learner diversity

• Cultural

diversity

• Social and

political

influence

• universal

principles of

learning

• cultural differences

(beliefs,

expectations

and values)

• individual

learning style

preferences

• Scenario based

learning

• Brainstorming

• Case study

• Discussion on administrative

rules and

regulations of

the affiliated

institution

• Scenario and

problems related to ethics of

examinations

• Writing

assistance and

other tutoring

• Role play on

ethical behavior

• Computer

ethics

• Use of academic

resources

• Respecting

the work of

others

• Use of

sources on

papers and projects

• Maintaining

standards

and making

research for

continuing

professional development

• Honesty and

integrity for

fulfilling

professional

responsibilities

• Pursuing

appropriate

measures to

correct

regulations

that are’ t in

conformity with sound

educational

goals

• Adherence

to academic

regulations

PO9

• Ability to demonstrate

pro-activeness,

professional leadership

and appreciate societal

and environmental

implications of decisions

• Indirect

solutions on

the given

problem

• Complex

decision

making process

• Projects

• Presentation

• Group

Discussion

• Cooperative

Learning

• Problem-based

Learning

• Competition

• Invited speakers

• Service learning

• Field trip

• Staff

participation

s / support

• Cooperation

• Ethics

• Professionali

sm


• Face-to-Face Learning

- Lecturer-Centered Learning

i. Lecture

22

- Student-Centered Learning (SCL)


ii. Student-centered learning activities – Active Learning, Project Based Learning

-

20

• Self-Directed Learning

- Non-face-to-face learningor student-centered learning (SCL) such as manual, assignment, module,etc.

a. NALI

b. MOOCS

c. Blended Learning

22

-

25

- Revision 10

- Assessment Preparations 11

• Formal Assessment

- Continuous Assessment 10

- Final Examination 0

Total (SLT) 120

Weekly Schedule

Week Topics

Week 1-2

Social Network Analytics Overview and mini project overview

• Various definitions and Tools

Week 3-4

Week 5

Week 6-7

Week 8

Survey Research Overview including open-ended vs close-ended questions

• Common Uses

• Social Network Analytics Research Discussion

Content Analysis & Pattern Recognition

• Discovering the types of pattern, method and technique

Data Extraction

• Analyzing the information extraction for logical reasoning to draw

inferences from natural, unstructured communication

• Understanding the root causes of communication problems

Data Reduction And Document Libraries

Mid Term Exam

Group Project Discussion

Week 9

Week 10-12

Taxonomy And Classification Social Network Analytics using R

• R Workshop - Downloading/importing data in R - Transforming Data / Running queries on data - Basic data analysis using statistical averages - Plotting data distribution

• Lab Work: Network Graph Analysis and Visualization

Week 13

and 14

Week 15

Recent achievements in the field and its related issues

• Discussing and introducing recent issues

Project Presentation and Evaluation

Week 16-18 Revision Week and Final Examination

GRADING

No Assessment %Total

1 Term Paper 30

2 Report 10

3 Assignment x 2 30

4 Observation 5

5 Self Reflection 5

6 Project 10

7 Presentation 10

Total 100%

REFERENCES

1. Cutroni, Justin. Google Analytics. 1 edition. Beijing, China; Cambridge, MA:

O’Reilly Media, 2010.

2. Miller, Thomas W. Modeling Techniques in Predictive Analytics: Business

Problems and Solutions with R. 1 edition. Upper Saddle River, New Jersey:

Pearson FT Press, 2013

3. Barabási, A.L. and Pósfai, M., 2016. Network science. Cambridge university

press.

4. Newman, M., 2010. Networks: an introduction. Oxford university press.

Prepared By

Name : Dr. Pritheega Magalingam

Signature :

Date : 11 August 2016

Certified By

Head of Department

Name : Dr.Nazri Kama

Date : 11 August 2016

COURSE OUTLINE

Department & Faculty:

Advanced Informatics School

Universiti Teknologi Malaysia

Page : 1 of 6

Course Code: MANA 1533 –Enterprise Information Assurance Total Contact Hours: 42

Semester: 1 Academic Session: 2017/2018

Prepared by: Name: Dr. Pritheega Magalingam Signature: Date: 12/8/2016

Certified by: (Course Panel Head) Name: Signature: Date:

Lecturer : Dr. Pritheega Magalingam

Room No. : 07.40.01

Telephone No. : 03- 2203 1442


Synopsis : The purpose of enterprise information assurance and management strategy is to protect an organization’s valuable assets and resources, such as information, people and services. Through the selection and application of appropriate safeguards and control helps the organization meet its business objectives or mission by protecting its physical and financial resources, reputation, legal position, employees, and other tangible and intangible assets. This course will examine the elements of information security assurance, employee roles and responsibilities, and common threats. It also examines the need for management controls, policies, procedures, and strategy. Finally, this course will present a comprehensive list of tasks, responsibilities, and objectives that make up a typical information protection program.

LEARNING OUTCOMES By the end of the course, students should be able to:

No. Course Learning Outcome Programme Outcome

Taxonomies (C, P, A)

Weightage (%)

Assessment Methods

CO1 (a) Relate and examine the important technical and management terminology, concepts, principles, techniques, and theories related to information assurance management.

(b) Integrate and extend high order thinking skills to the professional practices in the information assurance disciplines.

PO1

C1-5, P1-5, A1-5,

40% A=5%,Q=5%,Pr=5%, F=15%, T=10%

CO2 (a) Discover and demonstrate PO2 C3, P4, P5, 20% A=5%,PR=5%, F=10%


COURSE OUTLINE

Department & Faculty: Page : 2 of 6

Course Code: MANA 1533 –Enterprise Information

Assurance Total Lecture Hours: 42


important technical and management concepts, principles, practices, techniques, and theories through an appropriate research skill to design an organization’s information assurance and management requirements.

LL1-2

CO3 (a) Analyse a real world problem and demonstrate critical thinking.

(b) Investigate the given problem, apply knowledge and show creative problem solving ability.

PO3 C4, P2, P3, P4, P5, A2, A3, A4, LL2

20% F=15%,T=5%

CO4 (a) Plan and role-play to intergrate information assurance professional ethics in the professional, organization and society.

PO4 C5, A4, LL2 10% Pr=5%, RW=5%

CO5 Ability to develop cooperative network and team working

PO8 C5, A4, LL2 10% Pr=5%, RW=5%

(A – Assignment; T – Test ; PR – Project ; Q – Quiz; SR- Self Reflection; HW – Homework ; Pr – Presentation; F – Final Exam; RW-Report Writing) STUDENT LEARNING TIME (SLT)


1. Face-to-Face Learning

a. Lecturer-Centered Learning

i. Lecture

18

b. Student-Centered Learning (SCL)


ii. Student-centered learning activities – Active Learning, Project Based Learning

24

2. Self-Directed Learning

a. Non-face-to-face learning or student-centered 37

COURSE OUTLINE





learning (SCL) such as manual, assignment, module, etc.

b. NALI/MOOCs/e-Learning 10

c. Revision 8

d. Assessment Preparations 8

3. Formal Assessment

a. Continuous Assessment 12

b. Final Exam 3

Total (SLT) 120

PO

SCHOLARSHIP

OF KNOWLEDGE

LEARNING

ENVIRONMENT

TEACHING AND LEARNING

METHODS

ASSESSMENT

CRITERIA

ASSESSMENT

METHOD

PO1

Advanced Knowledge

Ability to demonstrate higher order thinking skill and view things in broader perspective

Ability to produce work of scholarly quality.

Involve discussions

Critic ideas

Real practices

Think scholarly

Cooperative learning

Case study

Group Discussion

Problem-based Learning

Constructivist Approach

Paper Critique

Knowledge sharing

Intellectual discourse

Subject Knowledge

Pedagogical Knowledge

Commitment to Personal Growth

Teaching Effectiveness

Quiz

Assignment

Examination

Presentation

Academic Writing

Self-Reflection

reflective critique

PO2

Research Skills

Ability to apply appropriate research methodologies and techniques within the discipline;

Ability to

Involve higher order thinking

Work / Lab setting

Multi disciplinary knowledge

Article Critique

Mini Research/ action research

Project work

Simulation

Seminars/Conferences

Mentor-mentee researcher

Systematic review

Research methods

Scope of the research

Research contribution

Oral examination (viva)

Assignment

Project report

COURSE OUTLINE





integrate existing and new ideas into established knowledge

Practicality

Relevant research areas

PO3

Critical Thinking

Ability to demonstrate critical thinking and creative problem solving;

Involve discussions

Critic ideas

Experiential

Create hypothesis

Think scholarly

Cooperative learning

Case study

Guided Lectures

Group Discussion

Problem-based Learning

Constructivist Approach

Paper Critique

Knowledge sharing Intellectual discourse

Subject Knowledge

Commitment to Personal Growth

Teaching Effectiveness

Quality of Innovation

Quiz

Assignment

Examination

Presentation

Academic Writing

Self-Reflection

reflective critique

PO4

Ethics, Values,

Professionalism

Possess a profound respect for truth, professional and intellectual integrity and ethics of research and scholarship;

Meta-thinking

Respect for truth

Involve personal goal

Honesty and integrity for fulfilling professional responsibilities

Learner diversity

Cultural diversity

Scenario based learning

Brainstorming

Case study

Discussion on administrative rules and regulations of the affiliated institution

Scenario and problems related to ethics of examinations

Computer ethics

Giving assistance to others

Collecting and reporting data

Use of academic resources

Respecting the work of others

Use of sources on papers and projects

Adherence to academic regulations

Self reflection

Observation

Interview

COURSE OUTLINE





TEACHING METHODOLOGY

Constructivism Learning through lecture, e-forum, quiz, scenario analysis, case studies, class presentation, Jigsaw activity and class discussions based on current recommended information assurance practices.

WEEKLY SCHEDULE

Week 1 : Lecture 1: Discovering What to Secure

Week 2 : Lecture 2: Assessing Risk

Week 3 : Lecture 3: Security Policy

Week 4 : Lecture 4: Building and Documenting an Information Assurance Framework

Active Learning:

-Forum Discussion 1, Assignment 1 (Individual) and Quiz 1 using e-learning

-Jigsaw classroom (Lec 1-4) & Discussions

Week 5 : Lecture 5: Maintaining Security of Operations

Week 6 : Lecture 6: Ensuring Controlled Access

Week 7 : Lecture 7: Personnel Security

Week 8 : Mid-Semester Break

Week 9 : Lecture 8: Physical Security

Week 10 : Lecture 9: Assuring Against Software Vulnerabilities

Active Learning:

-Forum Discussion 2, Quiz 2 & Assignment 2 (Group-Case Study Project) using e-learning

Week 11 : MidTerm Test (Lec1-9)

Lecture 10: Continuity Planning and Disaster Recovery

Week 12 : Lecture 11: Law, Regulations, and Crime

Active Learning:

-Assignment 3 (Individual) using e-learning and Class Discussion

Week 13 : Lecture 12: Network Security Basics: Malware and Attacks

Week 14 : Lecture 13: Cryptology

Week 15 : Lecture 14: Ensuring the Secure Use of Software

Week 16 : Lecture 15: Human Factors: Ensuring Secure Performance

Lecture 16: Information Ethics and Codes of Conduct

COURSE OUTLINE





Active Learning: -Oral Presentation, Report Writing and Class Discussion

Week 17 -18 : Revision Week and Final Examination

REFERENCES :

1. Management of Information Security, by Whitman and Mattord, 2004, Thomson Course Technology, ISBN 0-619-21515-1.

2. Information Assurance: Managing Organizational IT Security Risks, by Joseph Boyce and Dan W. Jennings, 2006, Elsevier Science, ISBN-0-7506-7327-3

3. Information Assurance for Enterprise, by Corey Schou and Daniel Shoemaker, 2006, Mc-Graw Hill. 4. Thomas R. Peltier, Justin Peltier, and John Blackley, Information Security Fundamentals, Auerbach

Publications, 2005, CRC Press. 5. Merkow, M., and Breithaupt, J. (2006), Information Security Principles and Practices, New Jersey: Pearson

Prentice Hall. 6. Alan Calder and Steve Watkins. IT Governance: A Manager’s Guide to Data Security and ISO 27001/27002

4th Edition 2008; ISBN 978 0 7494 52711 7. ENGINEERING INFORMATION SECURITY: The Application of Systems Engineering Concepts to Achieve

Information Assurance by Stuart Jacobs, IEEE Press & John Wiley, Copyright: 2011. 8. Information Assurance: Managing Organizational IT Security Risks, by Joseph Boyce and Dan W. Jennings,

2006, Elsevier Science, ISBN-0-7506-7327-3 GRADING:

No. Assessment Number %each %total

1. Assignment 2 5 10

3. Project (Group-Case-based Learning) -Oral Presentation -Report Writing -Peer Review

1 30 30

4. Quiz 1 5 5

5. MidTerm Test 1 15 15

8. Final Exam 1 40 40

Total 100 100

Appendix II– A Sample of Course Assignment

Prepared by Dr. Pritheega Magalingam Sem22018/2019 Page 1

SEMESTER 2, 20182019

Assignment 1 (10%)

Individual Assignment

CLASS: MANB 2163 Social Network Analytics TYPE: Full Time-01

Date: 8/3/2019 Submission Date: 27 /3/2019

1) Refer to the Figure 1 below:

Figure 1: Net A

The Net A above is a directed network. Write down the adjacency matrix of the network

above. Redraw the network as undirected network and find the path matrix.

2) Network Analysis using software tool: Gephi

• Go to Facebook - You can use the Lost Circles plugin for Chrome. Use that and

then click the download option to get your dataset which you can then open in

Gephi. You must use Gephi for this exercise.

• You have learnt Gephi in the class lab. Use Gephi to analyse the dataset and

answer the following questions:

o Plot the Facebook network and visualize it.

o Choose different layout and display it.

1

3 2

4 5

https://chrome.google.com/webstore/detail/lost-circles-facebook-gra/ehpmfdlcppenimpibdifodjgfafkjhjl?hl=en


o Show the network as directed and undirected. For the undirected network

remove the multiple link edges and loop if the is any.

o Describe what “average path length” of a network is. Calculate the

average path length of the Facebook network.

o Describe what “diameter” of a network” is. Calculate the diameter of the

Facebook network.

o State the definition for degree, in-degree and out-degree of a node.

o Go to your network and show labels. Then rank the nodes based on:

➢ In-degree and show which node has the highest in-degree.

➢ Out-degree and show which node has the highest out-degree.

➢ Degree and show which node has the highest degree.

o Identify the important node based on degree (use color) and display it.

➢ Which is the most important node? Describe the node’s position

and explain why it is the most important.

o Identify the important node based on highest betweenness centrality (use

color) and display it.

➢ Which is the most important node? Describe the node’s position

and explain why it is the most important.

o Size the node by betweenness centrality and color coding by the

modularity class (by cluster). Display the network.

➢ Explain the formation of components within the network. Show how

to identify components and the number of components that exist?

o Identify community within the network by using two different

parameters/data (don’t use modularity class). State which parameter/data

you use, display the network and explain the strongly connected and

weakly connected nodes in each of the network separately.

o Analyse the network more by filtering the network based on three different

parameters. Display each network separately, explain why you use

choose the parameter and what you could conclude from the network.

o Make sure you save your file xxx.gephi and keep the file for further

analysis in your next assignment.


Grading

10 points: quality of writing 30 points: quality of analysis 10 points: quality of visualization

Assignment Format:

File format • The assignment should be written using MS Word with format: .doc, .docx. This

document should show your discussion, analysis and visualization for each question where relevant.

Fonts

• Use a clear, readable, sans serif font such as Verdana, Calibri, Tahoma or Arial, and be consistent and use the same font throughout.

• Use 11 or 12 point for the body of your assignment.

Spacing

• Use 1.5 or double spacing and fairly wide margins. This leaves room for the marker’s comments.

• Leave a blank line between paragraphs. • If the questions are short, leave a blank line between each question. If they are

long, start each question on a new page. • Left-justify your work (also known as left-aligned). Block-justified (flush left and

right) might look tidy, but it’s harder to read as it can result in gaps between words.

Headings

• Use bold for headings. Not underlining or italics.

Title page

This assignment requires a title page, which should include the following:

• the title and number of the assignment • the course number and name • the due date • your full name and student number. • your lecture’s name

This information should be centered, starting approximately one third of the way down the page.


Numbering

• Number all pages except the title page. • Tables and figures must be numbered and clearly labelled. Table captions

are placed above the table, while captions for a figure go below the figure.

Reference list

The reference list comes at the end of the assignment, and should start on a new page labelled 'References'.

Appendices

Appendices are used for information that:

• is too long to include in the body of your assignment, or • supplements or complements the information you are providing.

Start each appendix (if applicable) on a new page. If there's just one appendix label it ‘Appendix’ without a number, but if there are more than one label them Appendix A, Appendix B, etc. In the main text of your assignment, refer to the Appendix by the label, e.g. Appendix A.

Stapling your assignment

• Staple multi-page assignments in the top left corner only. • Don’t put your assignment in a plastic folder.

-End-


Assignment 2 (20%)


CLASS: MANB 2163 Social Network Analytics TYPE: Part Time-01

Date: 27/3/2019 Submission Date: 21/4/2019


Network Analysis and Visualization with R and igraph

Find a dataset (a large network). The dataset that you choose must have labels/names for each

node. Each student must select a unique set of data. You can use the following links to find your

data:

• https://github.com/gephi/gephi/wiki/Datasets

• http://snap.stanford.edu/data/

• http://socialcomputing.asu.edu/pages/datasets

Make sure you cite the source of the dataset that you choose. Show how you analyze the data based

on the instructions given below. Show R script for all the activities.

Plotting Network using igraph

1. Explain the data fields. Choose the specific data fields that you want to use to build the

network.

2. Read the network data from csv files and display the data in a table in R.

3. Plot the network using igraph.

4. Examine the data:

a. Find number of nodes

b. Find number of edges

c. Find the edgelist (“from”, “to”)

5. Simplify the network by removing all the multiple edges and loops.

6. Extract the adjacency matrix of the network and display.

7. Replace the vertex labels (auto label) of each node with the node names stored in the data

table.

8. Generate node color based on the type of nodes. For example, different group of people

belongs to different type of sports are visualized using different colors. Add legends to

explain the meaning of colors.

https://github.com/gephi/gephi/wiki/Datasetshttps://github.com/gephi/gephi/wiki/Datasetshttp://snap.stanford.edu/data/http://snap.stanford.edu/data/http://socialcomputing.asu.edu/pages/datasetshttp://socialcomputing.asu.edu/pages/datasets


Assignment 2 (20%)





9. Set the node size based on the degree of the node.

10. Use 5 different type of layouts in igraph to plot the network and display it. Explain the

changes in the network structure and compare your network based on the different layout

algorithm that you have used.

11. Give a degree range for the nodes you want to explore and keep only the nodes that ties

between the chosen range. Display the network. Display the evolution of network by

changing the node degree range till you get a network with separated components.

Network and node descriptions

1. Using the same network (simplified network), find the density of the network.

2. Find the number of triangles formed in the network.

3. What is the diameter of the network?

4. Color the nodes along the diameter which means color only the nodes that pass through the

longest shortest path.

5. List the degree of nodes and display it in a table. Create a histogram of the node degree.

6. Find the degree distribution of the network and display it in a dot graph.

Centrality Values

1. Rank the nodes based on degree, betweenness, closeness and eigenvector centrality value

and display it in a table.

2. Find the nodes with highest degree, betweenness centrality, closeness and eigenvector

centrality values.

3. Find the hubs in the network and display each of it in a different color.


Assignment 2 (20%)





Distance and paths

1. Calculate the average path length for both (undirected and directed network).

2. Using the undirected network, find all the shortest paths from one node to another and the

length of all shortest paths in the graph.

3. Find the shortest path from the node with highest betweenness centrality (broker) to all

other nodes. Color the path that has the longest shortest path from the broker to its

destination node. Repeat the same for nodes with highest degree and eigenvector centrality

values.

4. Identify the immediate neighbours of the node with highest degree centrality value. Set

colors to plot the neighbours. Display the network and explain the neighbours with this

important node.

5. Identify the immediate neighbours of the node with highest eigenvector centrality value.

Set colors to plot the neighbours. Display the network and explain the neighbours with this

important node.

Subgroups and communities

1. Find cliques in the network and display it. How many cliques that you can find in the

network?

2. Find a community detection algorithm in igraph. Explain how it works. Apply the

community detection on your network and display the network. Each community must be

in its own color.

a. Find the number of communities that occur.

b. Find its membership

c. Find how modular the graph partitioning is. (High modularity for a partitioning

reflects dense connections within communities and sparse connections across

communities)


Assignment 2 (20%)





Grading

10 points: quality of writing 30 points: quality of analysis 10 points: quality of visualization



Class Project (10%) Presentation (10%)

CLASS: MANB 2163 Social Network Analytics TYPE: PART TIME-02


Instruction: Based on our research paper activity in class, choose a journal paper that is related to social

network analysis. Find the datasets that have been used by the author. Understand the research done

and create your own questions/research questions (each group must create three questions) based on

the paper that you have chosen above. The area you want to explore must be different from the output of

that journal paper. Use the social network analysis techniques (R programming and Gephi or R

Programming only) that have been taught in the class to answer your research questions. Your analysis

using the technique should provide a new finding.

Format: Follow the same format as the journal paper that you have found to complete your project. See

sample format sample given in the attachment of this project in the elearning. Typically, your paper

should include the following:

Abstract – 5 points

Introduction – 10 points

Related Work – 20 points

The Data Set – 5 points

Methodology/Analysis – 25 points

Experiment Results – 25 points

Conclusion – 10 points

Minimum number of pages:12

Grading: (100 points)

Grading will be based on the quality of writing, quality of analysis, results, content of your paper and the

originality of your work. The 100 points is worth 10% of your total marks.

Submission List:

a) Research Paper (Hardcopy on the day of presentation)

b) Softcopy in ELearning

c) Please ensure that your paper's similarity rating is less than 20%. Please attach your similarity

report (Turnitin report) together when you submit your assignment.

*** A class presentation related to this project will be held on the 14th April 2019. Presentation marks

(10%).

Class Presentation Assessment Rubric

MANB 2163 Social Network Analytics Semester 2, 20182019

Name: Matric Number:

Bil SCALE 8-10 6-7 4-5 0-3 Weight Score

CRITERIA Excellent Good Pass Fail

1 Eye Contact Holds attention of entire audience with the use of direct eye contact and seldom looking at notes.

Direct eye contact with audience, but frequent returns to notes.

Displayed minimal eye contact with audience, while reading mostly from the notes.

No eye contact with audience, as entire report is read from notes.

/10

2 Enthusiasm Shows a strong, positive feeling about topic during entire presentation.

Occasionally shows positive feelings about topic

Shows some negativity toward topic presented

Shows absolute no interest in topic presented.

/10

3 Elocution Student uses a clear voice and correct, precise pronunciation of terms so that all audience members can hear presentation.

Student’s voice is dear. Student pronounces most words correctly. Most audience members can hear presentation.

Student’s voice is low. Student incorrectly pronounces terms. Audience members have difficulty hearing presentation.

Student mumbles, incorrectly pronounces terms, and speaks too quietly for a majority of students to hear.

/10

4 Subject Knowledge

Demonstrates full knowledge by answering all class questions with explanations and elaboration.

Student can answer all questions, without elaboration.

Student is not well versed with information and is able to answer only rudimentary questions.

Student does not have grasp of information; student cannot answer questions about subject.

/10

5 Organization The presentation is well structured, logical with interesting sequence that audience can follow and understand.

The presentation follows logical sequence that audience can understand.

The presentation is difficult to be understood because student jumps around.

The presentation cannot be understood because there is no sequence of information.

/10

6 Slides Appropriate font, size, text, background color. Relevant and clear diagram/picture Animated appropriately, has some additional features.

Most font, text size, and background colour are appropriate, relevant diagrams /pictures included, partly animated but no additional features

Slides prepared half hazardly, some font, text and background colour were not appropriate, minimum diagram/pictures, no animation or additional features

No or poorly prepared slides, text and pictures cannot be understood, no animation at all

/10

7 Mechanics Presentation has no misspellings or grammatical errors.

Presentation has no more than two misspellings and/or grammatical errors.

Presentation has three misspellings and/or grammatical errors.

Presentation has more than three spelling and/or grammatical errors.

/10

8 Time Management

Finishes within the prescribed time with appropriate pacing.

Hurriedly finishes on time Time not properly managed Late and poor time management

/10

9. Appearances Dressed appropriate to occasion and one level above audience, well mannered, adequate greeting, punctual

Dressed appropriate to occasion with same level to audience, good mannered, greeting and punctual

Dressed casually, fairly mannered, greeting and last minute appearance

Dressed poorly, ill mannered, little or no greeting and late.

/10

10. References/ Sources

More than adequate references, up to date, properly cited, correct format

Adequate references, some may not up to date, correctly cited and formatted.

Not enough references, some are out dated, cited but not consistent, not properly formatted.

No or very little references and outdated and not properly cited and formatted.

/10

Total Points

ASSIGNMENT 1 (5%)

Ms. Jones notifies you that a former employee has used an

additional disk drive. She asks you to examine this new drive to

determine whether it contains an account number the employee

might have had access to.

The account number, 461562 belongs to the senior vice president

and is used to access the company’s banking service over the

internet.

To process this case, locate the C2Prj03.dd file you extracted to

your work folder and load it in ProDiscover.

Ms. Jones also wants to know whether the disk contains any

occurrences of the keyword “BOOK”.

Finally, use the ProDiscover report generator to document the

steps you took and write a memo summarizing your findings.

* (Format: Font: Times New Roman, Font Size: 12, Submission Date: 15/10/2018)44

ASSIGNMENT 2 (5%) Q1: At a murder scene, you have started making an image of a

computer’s drive. You’re in the back bedroom of the house, and a

small fire has started in the kitchen. If the fire can’t be

extinguished, you have only a few minutes to acquire data from a

10GB hard disk. As a computer forensic investigator, give your

options to secure data from the hard disk.

Q2: What does a logical acquisition collect for an investigation?

Q3: Discuss the problems that you should be aware of during a

remote acquisition.

Q4: How does ProDiscover Investigator encrypt the connection

between the examiner’s and suspect’s computer?

Font: Times New Roman, Font Size: 12

Submission Date: 22ndOctober 2018 (Submit Hardcopy and Softcopy)

31

ADVANCED INFORMATICS DEPARTMENT RAZAK FACULTY OF TECHNOLOGY AND INFORMATICS

UNIVERSITI TEKNOLOGI MALAYSIA

Prepared By: Dr. Pritheega Magalingam


Case Study (10%) Group Work

CLASS: MANA 1563

E-Crime Investigation and Incident Response Management


Case Description An organization with an Internet of Things (IoT) model has recently begun to notice anomalies in its application system. The organization’s IT officer has undertaken an initial check of the system log files. He founds that there are a number of suspicious entries and IP addresses with a large amount of data being sent outside the company firewall. They have also recently received a number of customer complaints saying that there is often a strange pop-up message displayed during order processing, and they are often re-directed to a payment page that does not look legitimate. The IT manager suspects that it could be a sabotage due to an increased competition in the hi-tech domain and is anxious to ensure that the organization’s system is not being compromised. Analysing a large-scale data on a social reaction or communication within the IoT environment is tedious and extremely time-consuming. A specific interaction pattern cannot be confirmed by the investigator as a standard pattern of behaviour or motif in the process of predicting an illegal activity in the IoT environment. The IT manager does not feel that his team members have the expertise to carry out a full scale digital forensic investigation. He appoints you as an expert to carry out a digital forensic investigation to see whether you can trace the cause of the problems. Deliverables:

(a) Find the current problems that occur during an illegal activity investigation for the IoT environment.

(b) Review and trace the type of e-crimes that occur within the IoT environment and describe the chronology of each illegal activity (attack).

(c) Find the methods used to collect evidence from the IoT environment from past literature and other valid articles. Do a comparison table of the advantages and disadvantages of the methods. For example, reality mining technique is one of the evidence collection methods for different IoT devices. Describe the method and write down its advantages and disadvantages.

(d) Develop a method that you will use to collect evidence and provide a reasoned argument as to why the particular developed method is relevant for your investigation.

(e) Discuss the type of data that you could collect using your method and its limitations. Build a database for the evidence that you could collect using your method.

(f) Provide a critical evaluation of the method that you use by describing and showing that the evidence you have collected is useful for the next step of investigation.

(g) Describe the evidence chain of custody of your investigation. Note: The assignment must be in MS Word file format only. Please ensure that your writing's similarity rating is less than 20%. Please attach your similarity report (Turnitin report) together when you send in your assignment.

ADVANCED INFORMATICS DEPARTMENT RAZAK FACULTY OF TECHNOLOGY AND INFORMATICS

UNIVERSITI TEKNOLOGI MALAYSIA

Prepared By: Dr. Pritheega Magalingam

Format: Fonts

• Use a clear, readable, sans serif font such as Verdana, Calibri, Tahoma or Arial, and be consistent and use the same font throughout.

• Use 11 or 12 point for the body of your assignment. Spacing

• Use 1.5 or double spacing and fairly wide margins.

• Leave a blank line between paragraphs. Headings

• Use bold for headings. Not underlining or italics. Numbering

• Number all pages except the title page.

• Tables and figures must be numbered and clearly labelled. Table captions are placed above the table, while captions for a figure go below the figure.

Reference list The reference list comes at the end of the assignment, and should start on a new page

labelled 'References'.

Avoid plagiarism.

GROUP ASSIGNMENT (20%) Search the internet for a cybercrime report or articles (case) related to computer

crime prosecutions. Write three to five pages summarizing the article based on

the question below.

(a) Describe the different types of computer crimes that have been carried out?

(b) Explain the chronology of event.

(c) What are the evidence to be produced?

(d)What are some of the challenges to the integrity of evidence in the case?

(e) Suggest the best evidence handling procedure for the case.

* Paperwork: (Format: Font: Times New Roman, Size: 12, Line space:1.5)

* Group presentation : (20 minutes each group, Submission and Presentation

Date: 11/10/2018)49

Appendix III List of attended seminar, conferences, workshops

and courses

Perincian Rekod Kehadiran Kursus -

Mata CPD (Staf)

No Pekerja : 11769 Nama Staf : PRITHEEGA A/P MAGALINGAM

Jawatan :

DS51A - PENSYARAH KANAN

(DS51) Fakulti :

K56 - FAKULTI TEKNOLOGI &

INFORMATIK RAZAK

Tahun Laksana :

Kod

Pelaksanaan Tajuk Jenis

Pering

kat Tahun Tarikh Tarikh

Mat

a

CPD

Mat

a

CPD

Kursus Kursus Kursus Kursus Laksana Mula Tamat

Kurs

us

Dap

at

1

AN/2017/2/0

0008/2017/0

2

SUPERVISORY EVALUATION

PACK (AS103)

PENASIHATAN DAN

PENYELIAAN

PASCASISWAZAH

PERT

ENGA

HAN 2017 4/6/2017 4/6/2017 6 6

2

AN/2017/3/0

0001/2017/0

2 KURSUS 'REMOTE SUPERVISION'

PENASIHATAN DAN

PENYELIAAN

PASCASISWAZAH

TINGG

I 2017 14/9/2017 14/9/2017 6 6

1

AA/2017/0/0

0009/2017/0

1

BENGKEL PENYEDIAAN BAHAN

PEMBELAJARAN OPEN

COURSEWARE (OCW)

PENGAJARAN DAN

PEMBELAJARAN 2017 22/3/2017 22/3/2017 6 6

1

E/2017/1/02

729/2017/01

TAKLIMAT GERAN UNIVERSITI

PENYELIDIKAN 2018

KURSUS/TAKLIMAT/BEN

GKEL/LATIHAN/SEMINAR

KHAS AWAL 2017 11/10/2017 11/10/2017 1 1

2

E/2017/1/02

751/2017/01

1 DAY WORKSHOP ON BLENDED

LEARNING USING E-LEARNING

23 AUGUST 2017

KURSUS/TAKLIMAT/BEN


KHAS AWAL 2017 23/8/2017 23/8/2017 3 3

3

E/2017/1/02

122/2017/01

TAKLIMAT INOVASI &

PENGKOMERSILAN OLEH

PENGARAH UTM ICC 9 OGOS

2017

KURSUS/TAKLIMAT/BEN


KHAS AWAL 2017 9/8/2017 9/8/2017 0.2 0.2

4

E/2017/1/01

664/2017/01

MAJLIS MENANDATANGANI MOU

DI ANTARA UTM DENGAN PDRM

& SYARAHAN PERDANA KETUA

POLIS NEGARA BERTAJUK

"CHALLENGES AND STRATEGIES

FOR THE NEXT DECADE"

KURSUS/TAKLIMAT/BEN


KHAS AWAL 2017 7/7/2017 7/7/2017 1 1

5

E/2017/1/01

453/2017/01

PROGRAM GOTONG-ROYONG

UTM AIS (PA3) 24 MEI 2017

KURSUS/TAKLIMAT/BEN


KHAS AWAL 2017 24/5/2017 24/5/2017 1 1

6

E/2017/1/00

978/2017/01

TEAM BUILDING & TACTICAL

PLANING '17 (UTM AIS

TeamTac'17) 3 & 4 April 2017

KURSUS/TAKLIMAT/BEN


KHAS AWAL 2017 3/4/2017 4/4/2017 16 16

7

E/2017/1/00

766/2017/01

"TALK" DUAL MASTERS DEGREE

(UTM-AIS) DEAKIN UNIVERSITY

AUSTRALIA 15 MARCH 2017

KURSUS/TAKLIMAT/BEN


KHAS AWAL 2017 15/3/2017 15/3/2017 1 1

8

E/2017/1/00

762/2017/01

AUDIT PEMATUHAN PROGRAM

PASCASISWAZAH UTM AIS 14

MAC 2016

KURSUS/TAKLIMAT/BEN


KHAS AWAL 2017 14/3/2017 14/3/2017 1 1

9

E/2017/1/00

431/2017/01

EnCase Essential V8 Training 14

Februari 2017

KURSUS/TAKLIMAT/BEN


KHAS AWAL 2017 14/2/2017 14/2/2017 1 1

10

E/2017/1/00

569/2017/01

Publication Workshop for PACIS

2017 7 Februari 2017

KURSUS/TAKLIMAT/BEN


KHAS AWAL 2017 7/2/2017 7/2/2017 3 3

PENGAJARAN DAN PEMBELAJARAN

PENYELIDIKAN DAN PENERBITAN

PERUNDINGAN DAN KEUSAHAWANAN

LAIN-LAIN

2017

Bil

3 HINGGA 10 TAHUN

Maklumat Staf

Maklumat Perincian Audit

No Pekerja : 11769 Nama Staf :

PRITHEEGA A/P

MAGALINGAM

Jawatan :

DS51A -

PENSYARAH KANAN

(DS51) Fakulti :

K56 - FAKULTI

TEKNOLOGI &

INFORMATIK RAZAK

Tahun Laksana :

Kod Pelaksanaan Tajuk Jenis Peringkat Tahun Tarikh Tarikh Mata CPD Mata CPD

Kursus Kursus Kursus Kursus Laksana Mula Tamat Kursus Dapat

1

E/2018/1/02828/2018/

01

BENGKEL

PENINGKATAN

PENERBITAN DALAM

JURNAL BERIMPAK

TINGGI RG

SOFTTRUST 5

DISEMBER 2018

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 5/12/2018 5/12/2018 3 3

2

E/2018/1/02236/2018/

01

AWARDS & CLOSING

CEREMONY -

RESEARCH WEEK

2018 19 OCTOBER

2018

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 19/10/2018 19/10/2018 1 1

3

E/2018/1/02235/2018/

01

CREATIVE WRITING

WORKSHOP -

RESEARCH WEEK

2018 18 OCTOBER

2018

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 18/10/2018 18/10/2018 3 3

4

E/2018/1/02233/2018/

01

POSTGRADUATE

ANNUAL RESEARCH

ON INFORMATICS

SEMINAR (PARIS

2018)-RESEARCH

WEEK 2018 17

OCTOBER 2018

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 17/10/2018 17/10/2018 3 3

5

E/2018/1/02400/2018/

01

INTERNATIONAL

GRADUATE

CONFERENCE ON

ENERGY,

ENGINEERING &

TECHNOLOGY 4 - 6

SEPTEMBER 2018

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 4/9/2018 6/9/2018 18 18

6

E/2018/1/02130/2018/

01

QUANTITATIVE DATA

ANALYSIS USING

SMART PLS

WORKSHOP 16-17

AUGUST 2018

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 16/8/2018 17/8/2018 6 6

7

F/2018/1/00047/2018/

01

PROFESSIONAL

DATA

HORTONWORKS

DATA PLATFORM

(HDP) DEVELOPER:

ENTERPRISE

APACHE PARK 7-10

AUGUST 2018

KURSUS

PEMBANGUNAN

PROFESIONAL AWAL 2018 7/8/2018 10/8/2018 24 24

8

E/2018/1/02216/2018/

01

TAKLIMAT

TRANSDICIPLINARY

RESEARCH GRANT

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 2/8/2018 2/8/2018 1 1

9

E/2018/1/01596/2018/

01

COMMERCIALIZATIO

N FUND TALK AND

ONE TO ONE

SESSION

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 17/7/2018 17/7/2018 1.5 1.5

10

E/2018/1/01781/2018/

01

HORTONWORKS BIG

DATA PLATFORM 13 -

21 MAC 2018

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 13/3/2018 21/3/2018 27 27

11

E/2018/1/00199/2018/

01

TEAM BUILDING &

TACTICAL PLANNING

2018 19 JANUARI -

21 JANUARI 2018

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 19/1/2018 21/1/2018 25 25

12

E/2018/1/00197/2018/

01

SESI PRA BENGKEL

PERANCANGAN

TAKTIKAL UTM AIS

2018 15 JANUARI

2018

KURSUS/TAKLIMAT/

BENGKEL/LATIHAN/S

EMINAR KHAS AWAL 2018 15/1/2018 15/1/2018 4 4

2018

Bil

No Pekerja : 11769 Nama Staf : PRITHEEGA A/P

Jawatan : DS51A - PENSYARAH KANAN (DS51) Fakulti :

K56 - FAKULTI TEKNOLOGI &

INFORMATIK RAZAKTahun

Laksana : Kod

Pelaksanaan Tajuk Jenis Peringkat Tahun Tarikh Tarikh

Mata

CPD

Mata

CPD

Kursus Kursus Kursus Kursus Laksana Mula Tamat

Kursu

s Dapat

1

Y/2019/1/00008/

2019/01

KURSUS TEACHING EXCELLENCE SYSTEM -

(TES) SESI PAGI - FTIR KL

KURSUS PENGAJARAN

MENGGUNAKAN TEKNOLOGI AWAL 2019 11/7/2019 11/7/2019 4.48 4.48

2

E/2019/1/01761/

2019/01 BENGKEL SEMAKAN KURIKULUM

KURSUS/TAKLIMAT/BENGKEL/LA

TIHAN/SEMINAR KHAS AWAL 2019 10/7/2019 10/7/2019 3 3

3

E/2019/1/01301/

2019/01

GLOBAL DIALOGUE - MALAYSIA - CANADA

PARTNERSHIP BY HER EXCELLENCY MS

JULIA G. BENTLEY HIGH COMMISSIONER OF

CANADA TO MALAYSIA



4

E/2019/1/01010/

2019/01

97th Professorial Inaugural Lecture Series

:Waste Management Through Anaerobic

Digestion - Opportunities and Challenges from

Malaysia's Perspective by Professor Dr. C.

Shreeshivadasan 18 April 2019



5

E/2019/1/00450/

2019/01

Town Hall Laluan Kerjaya Pelbagai Trek Staf

Akademik UTM (DCP) dan Laporan Penilaian

Prestasi Tahunan (LPPT-DCP) Siri 1/2019 di

UTMKL



6

E/2019/1/00468/

2019/01

TAKLIMAT DANA KOLABORASI

ANTARABANGSA UTM-MRUN



7

E/2019/1/00217/

2019/01

BENGKEL PERANCANGAN STRATEGIK &

TEAM BUILDING STAF AKADEMIK 2019 25-27

JANUARI 2019


TIHAN/SEMINAR KHAS AWAL 2019 25/1/2019 27/1/2019 11.5 11.5

2019

Bil

Appendix IV

Some students’ comments and feedbacks

7/26/2019 UNIVERSITI TEKNOLOGI MALAYSIA Mail - SNA review

https://mail.google.com/mail/u/0?ik=90d931ec80&view=pt&search=all&permthid=thread-f%3A1638733762634140267&simpl=msg-f%3A1638733… 1/1

PRITHEEGA A/P MAGALINGAM AIS

SNA review1 message

Muhammad Nidzam Maso'od Thu, Jul 11, 2019 at 12:11 PMTo: PRITHEEGA A/P MAGALINGAM AIS

Review

SNA is a very interesting subject that we can relate to our lives.The subject was taught in systematic and detail by Dr Pritheega. I also learned to code in R to solve SNA relatedproblems.

RegardsNidzam

7/26/2019 UNIVERSITI TEKNOLOGI MALAYSIA Mail - SNA Testimonial

https://mail.google.com/mail/u/0?ik=90d931ec80&view=pt&search=all&permmsgid=msg-f%3A1638746925181816064&simpl=msg-f%3A1638746… 1/1

PRITHEEGA A/P MAGALINGAM AIS

SNA TestimonialNURUL ATIEKAH BINTI AB RASHID MAN171036 Thu, Jul 11, 2019 at 3:40 PMTo: [email protected]

Dear Dr,

Please find below the subject SNA testimonial for your reference.

Social Network Analysis (SNA) is good for student to observe the relationship between the entities in the form ofvisual and mathematical analysis of human relationship. Your method is good in explaining the theories, visual anddefinition of the SNA. Your come up with the example and involving student to understanding the subject. However,the lack here is on the practical. You should show how the basic function of SNA software so that the students knowhow the software going to work. More software practical are encouraged to allow the students familiarity on SNA.Overall, you are doing great in delivering the SNA knowledge to your students.

Best regards,Atiekah

Testimony

ADITYA IYENGAR MAN171067 Sat, Jul 13, 2019 at 7:30 AM To: [email protected]

Hello Dr, I am attaching the testimonial that you had asked for. Thanks and Regards Aditya I

testimonial.docx 14K

Dr. Pritheega Magalingam was our Lecturer for the Social networking analytics

course. She is a very clear and concise instructor. She is knowledgeable, kind,

understanding, supportive, and detail oriented. She is also a good speaker and this

made her class feel comfortable in speaking up. She is very welcoming and ready

to help. She also explains course materials well. She is patient and willing to

explain a concept numerous times until students were able to grasp it. Her methods

of teaching and explaining things are well thought out and given at a level that the

students can understand. She takes the time in class and out of class to answer any

questions and help the students with any problems they may have.

Even though there were only 6 classes with great balance of theory and

practical strategies she was able to encapsulate the information and made sure the

students understood and the information was well researched. She made sure every

student is comfortable using different programming tools.

I would like to thank Dr. Pritheega for being patient towards us and

providing help to us whenever we have any questions and needed help the most,

and always trying her very best to make sure [that] each of us in the class

understands the problem and find a solution.

https://mail.google.com/mail/u/0?ui=2&ik=90d931ec80&view=att&th=16be887616557773&attid=0.1&disp=attd&realattid=f_jy0fgi1j0&safe=1&zw

Appendix V – Award Received

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