Course Structure Overview
The Cyber Security program at Chinmaya Vishwavidyapeeth is structured over eight semesters, with a balanced mix of core courses, departmental electives, science electives, and laboratory sessions. The curriculum emphasizes both foundational knowledge and specialized skills, ensuring students are well-prepared for advanced roles in the field.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| 1 | MATH101 | Mathematics I | 3-1-0-4 | None |
| 1 | PHYS101 | Physics | 3-1-0-4 | None |
| 1 | CHEM101 | Chemistry | 3-1-0-4 | None |
| 1 | ENG101 | English Language Proficiency | 2-0-0-2 | None |
| 2 | MATH102 | Mathematics II | 3-1-0-4 | MATH101 |
| 2 | CS101 | Introduction to Computer Science | 3-1-0-4 | None |
| 2 | CS102 | Programming Fundamentals | 3-1-0-4 | None |
| 2 | CO101 | Computer Organization | 3-1-0-4 | None |
| 3 | MATH201 | Mathematics III | 3-1-0-4 | MATH102 |
| 3 | DS101 | Data Structures and Algorithms | 3-1-0-4 | CS102 |
| 3 | OS101 | Operating Systems | 3-1-0-4 | CO101 |
| 3 | DBMS101 | Database Management Systems | 3-1-0-4 | CS102 |
| 4 | MATH202 | Mathematics IV | 3-1-0-4 | MATH201 |
| 4 | CS201 | Computer Networks | 3-1-0-4 | CO101 |
| 4 | SE101 | Software Engineering | 3-1-0-4 | DS101 |
| 4 | DM101 | Discrete Mathematics | 3-1-0-4 | MATH201 |
| 5 | CRYPTO101 | Cryptography | 3-1-0-4 | DM101 |
| 5 | SEC101 | Network Security | 3-1-0-4 | CS201 |
| 5 | INFOSEC101 | Information Security Principles | 3-1-0-4 | DM101 |
| 5 | SEC201 | Security Architecture | 3-1-0-4 | SEC101 |
| 6 | ETHICAL101 | Ethical Hacking | 3-1-0-4 | SEC101 |
| 6 | PENETRATION101 | Penetration Testing | 3-1-0-4 | ETHICAL101 |
| 6 | INCIDENT101 | Incident Response | 3-1-0-4 | SEC101 |
| 6 | CLOUDSEC101 | Cloud Security | 3-1-0-4 | SEC201 |
| 7 | MLSEC101 | Machine Learning for Security | 3-1-0-4 | CRYPTO101 |
| 7 | FORENSIC101 | Digital Forensics | 3-1-0-4 | INCIDENT101 |
| 7 | SECDEV101 | Secure Software Development | 3-1-0-4 | SE101 |
| 7 | COMPLIANCE101 | Privacy and Compliance | 3-1-0-4 | INFOSEC101 |
| 8 | FINALPROJECT101 | Final Year Project/Capstone | 6-0-0-6 | All previous courses |
| 8 | RESEARCH101 | Research Methodology | 3-1-0-4 | None |
| 8 | PROJECT101 | Capstone Project | 6-0-0-6 | All previous courses |
Advanced Departmental Elective Courses
Students in their later semesters can choose from a wide range of advanced departmental electives designed to deepen their expertise in specific areas of cyber security. These courses are taught by faculty members who are actively involved in cutting-edge research and industry consulting.
Machine Learning for Security (MLSEC101): This course explores how machine learning algorithms can be applied to detect anomalies, classify threats, and predict potential vulnerabilities. Students learn to implement models using frameworks like TensorFlow and PyTorch, while working on real datasets from actual security incidents.
Digital Forensics (FORENSIC101): The course provides an in-depth look at digital evidence collection, analysis, and reporting techniques. Students gain hands-on experience with industry-standard tools like EnCase, Autopsy, and Volatility, learning how to reconstruct events from compromised systems.
Secure Software Development (SECDEV101): This course focuses on secure coding practices, vulnerability assessment, and risk mitigation during the software development lifecycle. It covers topics such as OWASP Top 10, secure design principles, and code review methodologies.
Privacy and Compliance (COMPLIANCE101): Students examine various data protection regulations including GDPR, HIPAA, and CCPA, learning how to implement compliance strategies within organizations. The course includes case studies of regulatory violations and best practices for maintaining data integrity.
Cloud Security (CLOUDSEC101): This elective delves into cloud infrastructure security, including identity management, network segmentation, and compliance in multi-cloud environments. Students work with AWS, Azure, and GCP platforms to secure enterprise deployments.
Blockchain Security (BLOCKSEC101): This course explores the unique security challenges associated with blockchain technologies, covering consensus mechanisms, smart contract vulnerabilities, and decentralized application risks. It includes practical exercises on identifying and mitigating threats in blockchain systems.
IoT Security (IOTSEC101): Addressing the growing complexity of connected devices, this course examines security issues in IoT ecosystems, including device authentication, communication protocols, and firmware integrity checks.
Advanced Cryptography (CRYPTO201): Building upon foundational cryptography knowledge, students explore modern encryption techniques such as elliptic curve cryptography, homomorphic encryption, and quantum-resistant algorithms.
Cyber Threat Intelligence (CTI101): This course introduces students to the concept of cyber threat intelligence, focusing on gathering, analyzing, and disseminating actionable information about potential threats. It includes hands-on work with threat intelligence platforms like Recorded Future and Anomali.
Security Operations Center (SOC101): Designed for students interested in operational roles, this course covers the structure and function of SOC teams, including SIEM tools, incident response procedures, and security monitoring strategies.
Project-Based Learning Philosophy
The department strongly believes in project-based learning as a means to bridge the gap between theoretical knowledge and practical application. Students are encouraged to engage in both mini-projects and capstone projects that simulate real-world scenarios and challenges.
Mini-projects, undertaken during the second and third years, allow students to apply fundamental concepts learned in class to solve small-scale problems. These projects often involve collaboration with faculty members or industry partners, providing valuable networking opportunities.
The final-year capstone project is a significant undertaking that spans an entire semester. Students select topics aligned with their interests or industry needs and work closely with a faculty mentor throughout the process. Projects may result in patents, publications, or even startup ventures, making them a crucial part of student development.
Project selection involves a formal proposal phase where students present their ideas to a panel of faculty members. The evaluation criteria include originality, technical depth, feasibility, and potential impact. Once selected, students receive ongoing guidance from mentors and access to necessary resources including software licenses, lab time, and research funding.