11 citations · 14 across the 5 of their papers we have counts for
5 papers
Decision Theory-Guided Deep Reinforcement Learning for Fast Learning
Zelin Wan, Jin-Hee Cho, Mu Zhu +3
This paper introduces a novel approach, Decision Theory-guided Deep Reinforcement Learning (DT-guided DRL), to address the inherent cold start problem in DRL. By integrating decisi…
Honeypot Allocation for Cyber Deception in Dynamic Tactical Networks: A Game Theoretic Approach
Md Abu Sayed, Ahmed H. Anwar, Christopher Kiekintveld +1
Honeypots play a crucial role in implementing various cyber deception techniques as they possess the capability to divert attackers away from valuable assets. Careful strategic pla…
Cyber Deception against Zero-day Attacks: A Game Theoretic Approach
Md Abu Sayed, Ahmed H. Anwar, Christopher Kiekintveld +2
Reconnaissance activities precedent other attack steps in the cyber kill chain. Zero-day attacks exploit unknown vulnerabilities and give attackers the upper hand against conventio…
IoTFlowGenerator: Crafting Synthetic IoT Device Traffic Flows for Cyber Deception
Joseph Bao, Murat Kantarcioglu, Yevgeniy Vorobeychik +1
Over the years, honeypots emerged as an important security tool to understand attacker intent and deceive attackers to spend time and resources. Recently, honeypots are being deplo…
AIIPot: Adaptive Intelligent-Interaction Honeypot for IoT Devices
Volviane Saphir Mfogo, Alain Zemkoho, Laurent Njilla +2
The proliferation of the Internet of Things (IoT) has raised concerns about the security of connected devices. There is a need to develop suitable and cost-efficient methods to ide…