Comprehensive Course Listing Across 8 Semesters

Advanced Departmental Electives

The department offers a range of advanced elective courses designed to give students specialized knowledge in specific areas of cyber security:

• Cryptography and Network Security: This course explores the mathematical foundations of encryption algorithms, secure communication protocols, and cryptographic systems used in modern networks. Students learn about RSA, AES, and ECC algorithms while gaining hands-on experience with tools like OpenSSL.
• Malware Analysis and Incident Response: Designed for students interested in digital forensics, this course covers techniques for analyzing malicious code, identifying attack vectors, and responding to security incidents effectively. It includes practical sessions on reverse engineering using IDA Pro and Ghidra.
• Cloud Security and Compliance: This elective focuses on securing cloud environments using technologies such as AWS, Azure, and GCP. Students explore compliance frameworks like ISO 27001, NIST, and GDPR to ensure data protection in shared infrastructures.
• Cyber Policy and Governance: This course addresses the legal and regulatory aspects of cyber security, including international treaties, national laws, and ethical considerations. It includes case studies on major cyber incidents and their policy responses.
• Human Factors in Cyber Security: Understanding how human behavior impacts security is crucial for designing effective policies. This course examines cognitive biases, social engineering, and training strategies to reduce insider threats and improve overall organizational resilience.
• Artificial Intelligence for Cybersecurity: As AI becomes integral to both attacks and defenses, this course explores machine learning models for anomaly detection, threat prediction, and automated response systems. Students work with datasets from real-world security incidents.
• Security Architecture and Risk Management: This course teaches students how to design secure systems by understanding risk assessment methodologies, identifying vulnerabilities, and implementing appropriate controls. It emphasizes enterprise-level architecture planning.
• Digital Forensics and Incident Response: Students learn forensic techniques for recovering data from compromised systems and reconstructing cyber attacks. Emphasis is placed on legal admissibility of evidence and chain of custody procedures.
• Quantum Cryptography: As quantum computing advances, traditional cryptographic methods become vulnerable. This course explores quantum key distribution protocols and their implications for future security architectures.
• Security Testing and Penetration Testing: Through hands-on labs, students practice penetration testing methodologies using tools like Metasploit, Burp Suite, and Nessus to identify weaknesses in target systems before they are exploited by attackers.

Project-Based Learning Philosophy

The department strongly advocates for project-based learning as a core component of its pedagogical approach. Projects are structured to mirror real-world scenarios, allowing students to apply theoretical concepts in practical settings. The program includes two mandatory mini-projects during the third and fourth years, followed by a capstone project in the final year.

Mini-project 1 (Third Year): Students form teams of 3–4 members and select a topic related to network security or cryptography. Each team presents their findings in a formal report and an oral presentation before a panel of faculty experts. Projects are evaluated based on technical depth, clarity of documentation, and demonstration of problem-solving skills.

Mini-project 2 (Fourth Year): Building upon the first project, students refine their approach and implement solutions using industry-standard tools. The second mini-project involves collaboration with external partners, such as startups or government agencies, providing real-world exposure to current challenges in cyber security.

The final-year thesis/capstone project is a culmination of all learned skills. Students choose topics aligned with emerging trends, such as AI-powered threat detection, blockchain-based identity verification, or quantum-resistant encryption methods. Faculty mentors guide students through research methodologies, data collection, and analysis phases. The final deliverables include a comprehensive report, presentation slides, and a working prototype or simulation model.