Course offered at		Instructor
	The School of Data Science, Indian Institute of Science Education and Research Thiruvananthapuram, Thiruvananthapuram, Kerala, India	👤 Dr. Laltu Sardar ✉

Course Objective
This course builds a rigorous understanding of modern cryptography — from symmetric-key primitives, public-key systems and key infrastructure to the emerging challenges posed by quantum computing. Students will study the mathematical foundations of lattice-based post-quantum cryptography (including NIST-standardized schemes such as CRYSTALS-Kyber and CRYSTALS-Dilithium), and learn to apply cryptographic tools (liboqs, OpenSSL) to build secure, quantum-resistant systems. The course further examines security and privacy challenges specific to AI/ML systems — differential privacy, federated learning, secure aggregation and privacy-preserving inference — and how post-quantum cryptography can be integrated into modern AI/ML pipelines.

Prerequisites: DSC 314 or MAT 2012

Learning Outcomes:

• Explain the fundamental concepts, security definitions, and threat models of modern cryptography, including symmetric-key cryptography, public-key cryptography, hash functions, and MACs.
• Analyze the security challenges posed by quantum computing and the principles of post-quantum cryptography, including lattice-based assumptions and NIST-standardized schemes.
• Apply post-quantum cryptographic primitives and tools such as liboqs, OpenSSL, Kyber, and Dilithium for secure communication and hybrid cryptographic systems.
• Analyze security and privacy threats in AI/ML systems and compare privacy-preserving techniques used in secure AI/ML systems.
• Evaluate classical, post-quantum, and hybrid cryptographic solutions for secure system design with respect to security, performance, and deployment feasibility.

📃 Information

🗣 Announcements

📅 Class Schedule: Mid-Sem

📅 Class Schedule: End-Sem

📝 Assignments

📚 References