Rate My Professor Sanoop Mallissery

Sanoop Mallissery is a Lecturer in the School of Information Technology at Monash University Malaysia. A cybersecurity researcher and educator with over eight years of teaching experience and five years in industry, he specializes in securing software applications and detecting advanced cyber threats. He holds a Ph.D. in Computer Science from National Yang Ming Chiao Tung University, Taiwan, awarded on April 24, 2024, with his thesis titled "Securing Software Applications with Information Flow Tracking" under Prof. Yu-Sung Wu. His academic journey includes a Master's degree in Cyber Security, awarded August 1, 2010, with a thesis on "An Optimized Alert Correlation Engine for Enhanced Intrusion Detection," and a Bachelor's degree in Information Technology from the University of Calicut, awarded May 1, 2006, focusing on "Voice-Based Access Control for Secure Software Execution Based on Authorization."

Throughout his career, Mallissery has held positions including Assistant Professor at Manipal Institute of Technology, Manipal University, India; Research Fellow at ESIGELEC—IRSEEM, France, where he contributed to vehicular network security; Cyber Security Engineer at the Industrial Technology Research Institute (ITRI) in Taiwan; and Threat Researcher at TXOne Networks, Taiwan, securing ICS/OT environments. Currently, he integrates research-driven insights into teaching at Monash, exploring cybersecurity and privacy challenges. His research focuses on dependable software security and resilience, cybersecurity for critical infrastructure (ICS and OT), next-generation fuzzing for vulnerability detection, privacy protection in the data lifecycle, and AI-driven cyber threat detection. Notable publications include "Demystify the Fuzzing Methods: A Comprehensive Survey" (ACM Computing Surveys, 2023), "Pervasive Micro Information Flow Tracking" (IEEE Transactions on Dependable and Secure Computing, 2023), "Enriching the Semantics of Information Flow Tracking with Source-Level Memory Allocation Event Logging" (IEEE Conference on Dependable and Secure Computing, 2023), "Mixed-mode Information Flow Tracking with Compile-time Taint Semantics Extraction and Offline Replay" (IEEE DSC, 2021), and "Identification of data propagation paths for efficient dynamic information flow tracking" (ACM Symposium on Applied Computing, 2020). He has also developed tools such as PERMIT and SQUIRREL for information flow tracking. Mallissery accepts PhD students and welcomes collaborations on cybersecurity research and innovation.