Leveraging Generative AI for dynamic file honeypots in Windows Kernel
In the field of cyber security, dynamic file honeypots serve as critical tools for detecting and analysing malicious activities, especially zero-day ransomware attacks. This paper explores the integration of generative AI (GenAI) with file honeypots to enhance their effectiveness. By dynamically generating virtual decoy content, these advanced honeypots deceive attackers and protect real data. The discussion includes technical aspects of implementing file honeypots, focusing on two primary cases: dynamically inserted virtual honeypot files and honeypot files wrapped around real protected files. The paper also outlines the benefits of using GenAI for realistic content generation, continuous adaptation and enhanced threat intelligence. This approach not only bolsters security measures but also reduces storage footprints and improves overall cyber security resilience. operating in the region.
Vladimir Strogov – Acronis
Vladimir Strogov has 30+ years of experience in kernel level development in both storage and security areas (file systems, virtualization, data protection, reverse engineering, anti-malware solutions). He has worked on multiple Veritas and Symantec projects for nearly a decade. Additionally, he has worked at Kaspersky Lab in Core Drivers Group in roles of technical expert and team leads. Strogov is currently the Director of Development, Kernel Team at Acronis, having joined the team in 2016.
Sergey Ulasen – Acronis
Sergey Ulasen is Senior Director of AI Development at Constructor Technology, leading AI/ML/NLP research and development areas. He is the developer of the “Eugene Goostman” bot, the first ever bot to pass the Turing test. Ulasen is an expert in artificial intelligence computer systems with emphasis in natural language processing, speech recognition, image processing, and complex system modelling and research. He has 20+ years of experience in developing robust, scalable, and configurable commercial software for scientific and business applications. Ulasen developed the award-winning Natural Language Processing software.