Strategic Deployment of Honeypots in Blockchain-based IoT Systems
It addresses cybersecurity for Blockchain-based IoT systems, but appears incremental as it combines existing AI and game-theoretic methods for a specific domain.
This paper tackles cybersecurity in Blockchain-based IoT systems by introducing an AI-powered model for dynamic honeypot deployment, using game theory to predict attacks and strengthen security, though no concrete performance numbers are provided.
This paper addresses the challenge of enhancing cybersecurity in Blockchain-based Internet of Things (BIoTs) systems, which are increasingly vulnerable to sophisticated cyberattacks. It introduces an AI-powered system model for the dynamic deployment of honeypots, utilizing an Intrusion Detection System (IDS) integrated with smart contract functionalities on IoT nodes. This model enables the transformation of regular nodes into decoys in response to suspicious activities, thereby strengthening the security of BIoT networks. The paper analyses strategic interactions between potential attackers and the AI-enhanced IDS through a game-theoretic model, specifically Bayesian games. The model focuses on understanding and predicting sophisticated attacks that may initially appear normal, emphasizing strategic decision-making, optimized honeypot deployment, and adaptive strategies in response to evolving attack patterns.