Hash Functions

Abstract: Hash functions are now an essential part of cryptography, data science and cyber security. As part of the Cryptography course we will review their properties, try to develop our own hash function, explore how hash functions work in the real world and see some of their applications. This talk is suitable for all computing students from all backgrounds, although some knowledge of cryptography, Python scripting and bitwise operations will help you to get more out of this talk. If you want to prepare for this talk, you can read the book The Joy of Hashing by Thomas Mailund (the first three chapters) and The Theory of Hash Functions and Random Oracles by Arno Mittelbach and Marc Fischlin (chapters 1 and 2, especially section 2.3). Having your Python programming environment at hand (Google Colab or Kaggle) might also be useful. For those who want to use a GUI to experiment with hash and cryptography instead of programming, you can use CrypTool 2 from https://www.cryptool.org/en/ct2/.

Bio: Hassan Chizari is Professor of Computing at the University of Gloucestershire, Programme Leader of the MSc Cyber Security course and Research Lead for the School. Hassan holds a BSc in Computer Hardware from Shiraz University, Iran, an MSc in Artificial Intelligence and Robotics from the same university, and a PhD in Computing/Networking from Universiti Teknologi Malaysia. He did his PostDoc at Imperial College London in the area of medical implant security and randomness, which he continues to research. Hassan has more than 15 years of experience in higher education and teaching in various institutions around the world: IKIU - Iran; Singapore Institute of Management - Singapore; Universiti Teknologi Malaysia - Malaysia; Fachhochschule des Mittelstands - Germany; University of Derby, University of Gloucestershire and University of Warwick - UK. His teaching areas include networking (Cisco, SDN, ad hoc, forensic networking), programming, A.I., Big Data and IoT. His research has three focus areas: cybersecurity in extreme IoT devices (including medical implants); machine learning and graph theory; and last but not least, my main research focus is randomness extraction (especially from body physiological signals) and randomness testing.

Zoom Link: https://umass-amherst.zoom.us/s/99541192493  

                    Meeting ID:  995 4119 2493     Passcode:  467651