Electromagnetic Side-Channel Forensics to Detect AI-generated Video

Work in Progress

Digital Forensic, EM Side Channel Analysis

For my Undergraduate thesis, under the supervision of Arif Shakil Sir, We are working on Electromagnetic Site Forensics for Detecting AI-Generated Videos. With the growing concern of crimes facilitated by AI-generated videos, our research focuses on distinguishing between AI-generated and real mobile-recorded videos by analyzing their digital signal patterns. The goal of this work is to introduce a new forensic approach that can set boundaries against digital crimes and enhance the reliability of video evidence.

Case Study: Digital Photo Forensics – Verifying Viral Animal Images

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Digital Forensic, Photo Forensic

Two viral images, identified as picA and picB, circulated widely on Facebook and Instagram, claiming to show a newly discovered four-eyed animal in South Sudan. These posts gained rapid attention and were reshared thousands of times without verification. As part of Team Matrix’s Advanced Cyber Security Training Session, the task involves conducting a Digital Forensic Investigation to analyze the authenticity of the images, verify the accuracy of the claims, and determine whether the photographs have been digitally altered or misrepresented.

Case Study Analysis: Unfair Dismissal

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Artificial Intelligence, Ethics

This paper analyzes the case study “Unfair Dismissal” from The Ethics of Artificial Intelligence, focusing on [CO4] Social and Environmental Impacts and Sustainability, [CO5] Ethical Issues such as Bias, Transparency, and Accountability, and [CO6] Legal Implications and Engineer Responsibility. The wrongful termination of Ibrahim Diallo by an automated workforce system illustrates the dangers of over-reliance on AI without human oversight. The report highlights social, ethical, and legal implications, emphasizing responsible human-AI collaboration. This assignment is for the Artificial Intelligence (CSE422) course at BRAC University.

Python Programming Language -I

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CSE110

This course introduces foundational knowledge of string manipulation, arrays, control structure, file input/output, and the like. The debugging techniques and programming tools will make the students well-equipped in creating fundamental programs. From the anticipated outcomes of this course students will be able to Use flow control design tools, create flowcharts for solving problems. Write, debug, and execute programs using a programming language from hands-on experience & Apply branching and looping structures to control program flow, and implement conditional statements, loops, and basic programming concepts to solve simple problems.

Python Programming Language -II

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CSE111

This course would be an introduction to data structures, formal specification, and syntax of Object Oriented Programming (OOP), elements of language theory, and mathematical preliminaries. Other topics that would be covered are formal languages, structured programming concepts, and a survey of the features of existing high-level languages. Students would design and write applications using an appropriate language. The course includes a compulsory 3-hour laboratory work each week.

Data Structure

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CSE220

This course is an introduction to data structures, where the students will study the elementary data structures such as arrays, lists, stacks, queues, trees, etc. These data structures will be used to study and implement different algorithms such as sorting, searching, tree traversal, etc. The course includes a 3 hour mandatory laboratory per week as CSE220L. In the laboratory, the students will use a standard programming language, usually Java, to implement the various data structures and algorithms learned in the theory component of the course.

Algorithm Analysis & Design

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CSE221

This course addresses the study of efficient algorithms, their analyses and effective algorithm design techniques. Standard algorithm design strategies, such as, Divide and Conquer paradigm, Greedy method, Dynamic programming, Backtracking, Basic search and traversal techniques, Graph algorithms, Elementary parallel algorithms, Algebraic simplification and transformations, Lower bound theory, NP-hard and NP-complete problems are discussed in the course. Examples of data structures and algorithms studied in details are Heaps; Hashing; Graph algorithms: Shortest paths, Depth-first and Breadth-first search, Network flow, Computational geometry, Minimum Spanning Tree; Integer arithmetic: GCD, primality; polynomial and matrix calculations; Sorting; Performance bounds, asymptotic analysis, worst case and average case behavior, correctness and complexity. The course includes a compulsory 3 hour laboratory work every week.

Circuits and Electronics

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CSE250

Fundamental electrical concepts and measuring units of electrical charge, voltage, current, resistance, and power; Laws of electricity (Ohm's law, Kirchhoff's Current and Voltage law) and various methods of electrical circuit analysis (Nodal, Mesh); Introduction to basic electrical circuit elements; I-V characteristics; Circuit analysis in Direct current, First-order Transient and Alternating current mode, for various combinations of Resistive, Inductive and Capacitive networks; Phasor representation of sinusoidal quantities; Circuit theorems for linear circuits (Source Transformation, Superposition, Thevenin, Norton and Maximum Power Transfer). This course includes compulsory 3-hour laboratory work.

Digital Logic Design

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CSE260

This course provides an introduction to digital systems such as computer, communication and information systems. Firstly, the course will cover Boolean algebra, digital logic gates, combinational logic circuits, decoders, encoders, multiplexers and demultiplexers. The course will then cover sequential circuits: asynchronous and synchronous counters, registers, flip-flops. An introduction to memory elements and registers will also be provided. Hands-on experience will be provided through lab works and lab project. The course includes a compulsory 3-hour laboratory work each week.

Operating Systems

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CSE321

This course provides a general understanding of the principles and concepts governing the functions of operating systems and acquaints students with the state-of-the-art approaches that make the design, implementation, and operation of complex operating systems possible. The core of the course contains concurrent programming (threads and synchronization), inter-process communication, process and thread management, storage and resource management and communication, and an analysis on security and protection.

Numerical Methods

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CSE330

Fixed Point Arithmetic, Polynomial Interpolation, Differentiation, Nonlinear Equations, Linear Equations, Least-Squares Approximation, Numerical Integration

Automata and Computability

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CSE331

Alphabets, strings, and languages, Deterministic Finite Automata (DFA), Regular Languages, the Regular Operations, Regular Language closure properties, Nondeterminism, Nondeterministic Finite Automata (NFA), Equivalence between DFA and NFA using Subset Construction, Regular Expressions, Equivalence between Regular Expressions and Finite Automata, Converting Regular Expressions to NFA, Converting DFA into Regular Expressions using the State Elimination Method, Nonregular Languages, Pumping Lemma for Regular Languages, Context-Free Grammars (CFG) and Context-Free Languages (CFL), Parse Trees, Derivations, and Ambiguity, Chomsky Normal Form (CNF), the Cocke-Younger-Kasami (CYK) algorithm, Pushdown Automata (PDA) and its equivalence with CFGs, Turing Machines (TM), Turing-Recognizable and Turing-Decidable Languages, TM Variants, Undecidability, the Halting Problem, Reducibility.

MICROPROCESSORS

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CSE341

This course introduces the architecture, working mechanism and functionality of different microprocessors. This course primarily focuses on the Intel 8086 microprocessor’s architecture, its memory partitioning and registers, the instruction set, timing diagrams and its interrupt structure. Additionally, the concepts I/O addressing and the idea behind Direct Memory Access and its cascading are also discussed. Lastly, the course concludes with some concepts of the more advanced Intel 80x86 microprocessors and their basic architecture. The course includes a compulsory 3-hour laboratory work each week.

Computer Interfacing

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CSE360

This course will give an overview of computer interface components and their characteristics. It will cover detailed discussion on some programmable interfacing ICs, sensor, hardware, and software calibration on sensor interfacing, some processing devices which can interface computers with the real world and some output devices. This course also includes high power interface devices, LED, LCD, Seven segment display, transducers, stepper motors and peripheral devices. In addition, it will also introduce some software simulation tools to develop an interfacing system. Some advanced topics like Human Computer Interface (HCI), Brain Computer Interface (BCI) would be also discussed with some case studies.

Database

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CSE370

This course is designed as an introduction to relational database management systems (RDBMS) focusing on the efficient design, implementation and optimization of an RDBMS. Topics covered will include the advantages and disadvantages of DBMS, database architecture, data modeling using ER and EER models, relational integrity constraints, relational schema mapping from ER/EER, indexing, hashing and normalization. SQL Query formulation will be extensively practiced in both the theoretical and laboratory components of the course. The course includes a compulsory 3 hour laboratory work each week as CSE370L. Students must complete several hands-on SQL assignments and a group project for the laboratory work. The group project will involve the design and implementation of a complete database system including a user interface

Artificial Intelligence

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CSE422

Concepts of artificial intelligence, rationality, intelligent agents and their structures. Problem representation; task environments, search strategies, constraint satisfaction problems, constraint propagation, rule chaining, inference and learning in intelligent systems; systems of general problem solving, game playing, expert consultation, recognition, understanding and translation. Use of heuristic vs. algorithmic programming; cognitive simulations- vs. machine intelligence; study of some expert systems such as robotics and understanding. Solving problems in AI language.

Introduction to Robotics

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CSE461

This course introduces robotics by discussing basic laws, architectures, control systems, perceiving techniques, and communication. It will also investigate kinematics, motor action, mechanical engineering issues, advanced communication protocols and uses of AI in robotics.

Software Engineering

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CSE470

Introduces students to all aspects of SDLC. Make them familiar with standard practices and techniques in the software industry. It aims to reduce the gap between academic and industry practice. Projects by students where they analyze the requirements and develop a system with industry best practices.