Guest Lecture for Artificial Intelligence – Hardness of Learning Advanced Encryption Standard with Gradient-Based Methods by Purdue University

On May 22nd, 2024.  Binus University International’s Computer Science Program successfully held a Guest Lecture (GL) on Artificial Intelligence, titled “Hardness of Learning Advanced Encryption Standard with Gradient-Based Methods”, explored the challenges of using gradient-based methods to crack the Advanced Encryption Standard (AES) algorithm.

The event was moderated by Zhandos Yessenbayev, Ph.D., and featured Zhenisbek Assyibekov, Ph.D., a researcher from Purdue University, as the speaker. Dr. Assyibekov’s expertise lies in cryptography and applied mathematics, making him well-suited to delve into the complexities of learning AES with gradient-based methods.

The Advanced Encryption Standard (AES) is a widely used symmetric key encryption algorithm considered to be secure against various attacks. Gradient-based methods are a type of optimization technique commonly employed in machine learning. This guest lecture focused on the limitations and inherent difficulties associated with using gradient-based machine learning algorithms to learn or break the AES encryption.

This guest lecture provided a valuable opportunity for Binus University International’s computer science students and faculty to gain insights into the cutting-edge field of cryptography. By understanding the hardness of learning AES with gradient-based methods, students can learn more about cryptographic algorithms and how this knowledge can enhance data security.