IT Security University Course

In this IT Security course, I covered a wide range of important topics, gaining both theoretical knowledge and practical skills in cybersecurity.

I started with an introduction to identification protocols, which helped me understand how entities prove their identity in secure communications. Following this, I learned about commitments and zero-knowledge protocols, which are methods to verify the truth of a statement without revealing any additional information.

Next, I studied the ideal-real paradigm and universal composability, giving me a framework for analyzing and designing cryptographic protocols that remain secure under composition. I then focused on linear analysis, a mathematical approach used in the evaluation and design of cryptographic algorithms.

The course also included an in-depth look at code-based cryptography and the McEliece cryptosystem, particularly focusing on its security against adaptive chosen-ciphertext attacks. I explored post-quantum cryptography, preparing for the future landscape of cryptographic security in a world with quantum computers.

I also learned about side-channel analysis, which highlights techniques to protect cryptographic implementations from physical attacks. The lecture on complexity theory provided insights into the computational aspects of security, essential for understanding the limits and capabilities of cryptographic systems.

Towards the end of the course, I studied hashchain and cryptocurrency technology, exploring the principles behind blockchain and digital currencies. I also learned about privacy-preserving machine learning, teaching me methods to ensure data privacy in AI models.

The final lectures focused on biometric authentication, privacy and anonymity on the internet, and the use of machine learning for security purposes. The course concluded with an exploration of the security challenges in machine learning, preparing me to address these emerging threats in the cybersecurity landscape.