Bikash Saha
"Decoding Complexity, Securing Tomorrow."
"Decoding Complexity, Securing Tomorrow."
Bikash Saha is a Ph.D. candidate at the Indian Institute of Technology Kanpur, under the supervision of Prof. Sandeep Kumar Shukla. His research is centered on advancing Cyber Resilience through the application of Large Language Models (LLMs) in Cybersecurity. He focuses on developing intelligent, scalable systems that automate critical security tasks, including Malware behavior analysis, Threat intelligence extraction, proactive simulation of emerging attacks, and cybersecurity compliance assessment. His work explores how LLMs can understand attacker intent, reason over complex artifacts, and support decision-making in dynamic cyber environments, aiming to reduce analyst effort and enhance the adaptability of modern cyber defense.
Before joining IIT Kanpur, he completed his Master’s in Computer Science & Engineering from Indian Institute of Technology Bhilai, under the supervision of Dr. Rishi Ranjan Singh. Additionally, he gained industry experience as a Software Developer at Sterlite Technologies Limited.
📢 [01 May 2025] A book chapter titled "Generative AI in Financial Institution: A Global Survey of Opportunities, Threats, and Regulation" is up on Arxiv. [Paper]
📢 [22 April 2025] Recent paper titled "A comprehensive survey of advanced persistent threat attribution: Taxonomy, methods, challenges and open research problems" is accepted at the Journal of Information Security and Applications (JISA) [Paper] (Q1).
📢 [21 Mar 2025] Indian patent titled "SYSTEM FOR EXTRACTING MALWARE CAPABILITIES AND METHOD THEREOF" has been granted having Patent No.: 563203 .
📢 [28 Feb 2025] Recent paper titled "PARAG: Proactive Answering Framework Integrating LLMs with Retrieval-Augmented Generation" is accepted at the European Interdisciplinary Cybersecurity Conference (EICC 2025).
📢 [13 Jan 2025] Recent paper titled "MaLAware: Automating the Comprehension of Malicious Software Behaviours using Large Language Models (LLMs)" is accepted at the 22nd International Conference on Mining Software Repositories (MSR 2025) (Core A).
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