# AI in Cyber Security (v2: Minimal AI) **Course Code:** DI05032041-aics --- ## Course Information | Field | Details | | :--- | :--- | | Program | Diploma in Engineering | | Branch | Information & Communication Technology | | Level | Diploma | | Semester | 5 | | Academic Year | 2026-2027 | | Category | Professional Elective - II | | Prerequisites | Basic computer literacy (email, internet, mobile apps). No prior AI knowledge required. | --- ## Rationale In an era of pervasive digital connectivity, Cyber Security remains a vital shield against evolving threats. This course, "AI in Cyber Security," provides a foundational introduction to Cyber Space and its associated threats (malware, phishing, hacking), ensuring students from all backgrounds - including those who have not taken a dedicated security subject - can grasp essential security concepts. It covers core principles like the CIA triad, passwords, MFA, firewalls, and cyber laws (IT Act) alongside contemporary AI and Machine Learning (ML) techniques. While mastering traditional security principles and tools remains essential, students will also explore how AI can automate threat detection, improve malware analysis, and strengthen digital forensics. Simultaneously, the course addresses the emerging risks of AI-powered attacks and vulnerabilities in AI systems themselves. This hybrid approach ensures that ICT diploma students are equipped with both time-tested defensive strategies and the cutting-edge AI-assisted tools necessary for the modern security landscape. --- ## Course Outcomes After completion of the course, students will be able to: | No. | Course Outcomes | RBT Level | | :--- | :--- | :--- | | CO1 | Understand fundamental principles of cyber space, cyber threats, CIA triad, and cryptography, including AI's impact on data protection. | Understand | | CO2 | Implement security strategies for authentication, authorization, and defense against malicious software, incorporating AI-based detection. | Apply | | CO3 | Apply secure protocols for web, network, and system protection, utilizing AI for anomaly monitoring. | Apply | | CO4 | Conduct ethical hacking using Kali Linux tools, enhanced by AI-assisted vulnerability discovery. | Apply | | CO5 | Analyze cybercrimes and forensic evidence, addressing AI-driven threats like Deepfakes. | Analyze | --- ## Teaching and Examination Scheme | Teaching Scheme (Hours) | | | | Assessment Pattern (Marks) | | | | | | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | | **L** | **T** | **PR** | **C** | **Theory ESE** | **Theory CA** | **Practical CA** | **Practical ESE** | **Total** | | 3 | 0 | 2 | 4 | 70 | 30 | 25 | 25 | 150 | --- ## Course Content | Unit No. | Content | Hours | Weightage (%) | | :--- | :--- | :---: | :---: | | 1 | **Cyber Space, Threats & Cryptography Fundamentals**
1.1 Cyber Space and Cyber Security Foundation: Definition, CIA triad, and OSI Security Architecture.
1.2 Cyber Threats & Terminology: Overview of Cyber Threats (Internal vs External), Adversary, Attack, Risk, Asset, Vulnerability.
1.3 Private & Public Key Cryptography: Principles and use cases.
1.4 Hashing Algorithms: MD5 and SHA for data integrity.
1.5 **AI Application:** Role of AI in modern protection; how AI enhances and challenges traditional cryptography. | 8 | 18 | | 2 | **Account, Data & AI-Enhanced Security**
2.1 Authentication & Authorization: Password hygiene, Biometrics, Multi-factor auth (MFA), SSO, and CAPTCHA.
2.2 Malicious Software: Virus, Worm, Trojan Horse, Keylogger, Sniffer, Backdoor, Ransomware.
2.3 Defensive Measures: Firewalls (Packet filter, Application proxy), Antivirus concepts, Cloud security basics.
2.4 Account Attacks: Brute force, Social Engineering, Phishing (Vishing, Smishing), Machine-in-the-middle.
2.5 **AI Application:** AI in behavioral biometrics and AI-driven malware detection systems. | 8 | 18 | | 3 | **Network, System & AI-Powered Monitoring**
3.1 Web Security threats: Integrity, Confidentiality, Denial of service.
3.2 Network Ports & Protocols: Importance of ports, SSL/TLS, HTTPS, SSH, WAP security.
3.3 VPN (Virtual Private Networks): Secure remote access.
3.4 **AI Application:** AI for network traffic analysis, identifying botnets, and DDoS pattern recognition. | 8 | 18 | | 4 | **Ethical Hacking & AI-Assisted Penetration Testing**
4.1 Basics of Ethical Hacking: Types of Hackers, Hacking terminology (Vulnerability, Exploit, 0-Day).
4.2 Five Steps of Hacking: Info Gathering, Scanning, Gaining/Maintaining Access, Covering Tracks.
4.3 Introduction to Kali Linux: Footprinting, Port Scanning, Password Cracking, Injection attacks.
4.4 **AI Application:** Using LLMs (ChatGPT/Claude) for script auditing, vulnerability explanation, and security reporting. | 9 | 22 | | 5 | **Cyber Laws, Forensic & AI-Based Investigation**
5.1 Introduction to Cyber Crime: Types and classifications, Indian IT Act, Cyber Laws, and Digital Privacy.
5.2 Cyber Forensics: Overview, Disk, Network, Mobile, and Email Forensics.
5.3 Digital Forensics Tools: Autopsy, FTK Imager.
5.4 Basic Cyber Awareness & Practices: Password management, safe browsing, data privacy, incident reporting.
5.5 **AI Application:** AI-driven crimes (Deepfakes, AI-powered Phishing) and the use of AI in cyber forensic analysis. | 9 | 24 | --- ## Suggested Course Practical List | Sr. No | Practical Outcomes (PrOs) | Unit No. | Hrs. | | :---: | :--- | :---: | :---: | | 1 | Implement Substitution (Caesar Cipher) & Column Transformation in Python. | 1 | 2 | | 2 | Implement Private key Cryptography algorithm in Python. | 1 | 2 | | 3 | Implement MD5 and SHA hashing using Python. | 1 | 2 | | 4 | Simulate a brute-force attack to crack passwords and measure strengths (Python/Tool). | 2 | 2 | | 5 | **AI Application:** Use an AI assistant to analyze security logs and detect a failed login pattern. | 2 | 2 | | 6 | Set up Multi-Factor Authentication (MFA) and configure Antivirus/Firewall rules for protection. | 2 | 2 | | 7 | Use Nmap to scan a network and identify open ports on a system. | 3 | 2 | | 8 | Perform packet sniffing and password analysis using Wireshark. | 3 | 2 | | 9 | **AI Application:** Use an AI-powered tool or LLM to explain the traffic patterns observed in Wireshark. | 3 | 2 | | 10 | Basic Kali Linux commands and configuration in a virtual environment. | 4 | 2 | | 11 | Perform vulnerability scanning using Kali Linux tools. | 4 | 2 | | 12 | **AI Application:** Prompt an LLM to generate a secure version of a piece of vulnerable code. | 4 | 2 | | 13 | Perform forensic analysis (Registry/Artifacts) using FTK Imager or Autopsy. | 5 | 2 | | 14 | **Cyber Awareness:** Conduct/Prepare a cyber hygiene checklist or seminar on deepfake detection. | 5 | 2 | --- ## Suggested Specification Table with Marks (Theory) | Unit | Unit Title | R | U | A | N | E | C | Total | | :--- | :--- | :---: | :---: | :---: | :---: | :---: | :---: | :---: | | Overall Distribution | Theory Marks Distribution | 25 | 40 | 25 | 10 | 0 | 0 | 100 | **Legend:** R: Remember; U: Understanding; A: Application; N: Analyze; E: Evaluate; C: Create --- ## References/Suggested Learning Resources ### Books | Sr. No. | Title of Book | Author | Publication | | :---: | :--- | :--- | :--- | | 1 | Cryptography & Network Security | William Stallings | Pearson, 2019 | | 2 | Computer Security: Principles and Practice | William Stallings | Pearson, 2017 | | 3 | Hands-On Machine Learning for Cybersecurity | Soma Halder | Packt Publishing, 2018 | | 4 | Ethical Hacking | Daniel Graham | No Starch Press, 2021 | ### Open-source Software and Websites 1. [Udemy: AI in Cyber Security](https://www.udemy.com/course/ai-in-cyber-security/) 2. [IITM Pravartak: AI-Powered Cybersecurity Mastery](https://sl-courses.iitmpravartak.org.in/ai-cybersecurity-course-online) 3. [Coursera: AI for Cybersecurity Specialization](https://www.coursera.org/specializations/ai-for-cybersecurity) 4. [OWASP AI Security Guide](https://owasp.org/www-project-ai-security-guide/) 5. [NIST Artificial Intelligence Resources](https://www.nist.gov/artificial-intelligence) --- ## Suggested Student Activities 1. **Case Study Analysis:** Identify vulnerabilities in a real-world cyber attack. 2. **Hack-a-thon:** Participate in Capture The Flag (CTF) events. 3. **AI Tools Review:** Compare traditional Nmap scans with AI-assisted report generation. 4. **Cyber Awareness:** Conduct a seminar on deepfake detection. --- ## Laboratory/Learning Resources Required | Sr. No. | Laboratory/Learning Resources | Applicable To | | :---: | :--- | :--- | | 1 | **Computer System**
Windows 10/11 or Linux with 8GB RAM, Python 3.9+ Environment. | All PrOs | | 2 | **Software/Tools**
VS Code/Jupyter, Kali Linux, Wireshark, Nmap, Autopsy, FTK Imager, Access to LLMs. | PrOs 1-14 |