Muhammad Yousaf

Title Malware Detection using Fuzzy Hashes
Abstract

Cyber-attacks and the proliferation of malware is rising at a horrific rate. Availability of the open-source malware codes and the supporting tools to generate the malware variants have made it easy to create the malware whose signature is not previously known. This ease of creating malware has enticed many attackers and thus has resulted in the proliferation of malware. As traditional signature and hashing algorithms have been proven inadequate to detect malware, researchers have tried to design and use fuzzy hashes to counter the problem of detecting malware variants. Fuzzy hashes work to determine the similarity index of files or the sections of the file and thus can be used to compare the malware variants with the existing malware or malware families. This talk discusses the challenges in the detection of malware variants and potential benefits and limitations of using fuzzy hashes for malware detection.

Bio

Dr. Muhammad Yousaf is working as Associate Professor in the Faculty of Computing, Riphah International University, Islamabad, Pakistan. He is also serving as Head of Department, Department of Cybersecurity and Data Science, Riphah International University, Islamabad. He is a Certified Information Systems Security Professional (CISSP). He did his Ph.D. in Computer Engineering in 2013 from the Center for Advanced Studies in Engineering, University of Engineering and Technology (UET), Taxila. His research interests include network security, network forensics, traffic analysis, mobility management, and IPv6. In Riphah, he is leading the Network Security Research Group, where he is supervising many national as well as international R&D projects in the area of network and cybersecurity.