Strategic Deployment of Honeypots in Blockchain-based IoT Systems

TL;DR

This paper proposes an AI-driven, game-theoretic approach for strategically deploying honeypots in Blockchain-based IoT systems to improve security against sophisticated cyberattacks.

Contribution

It introduces a novel AI-powered, game-theoretic model for dynamic honeypot deployment in BIoT systems, enhancing adaptive cybersecurity measures.

Findings

Effective strategic honeypot deployment reduces attack success rates.

Game-theoretic analysis predicts attacker behavior and optimizes defense strategies.

Adaptive deployment improves resilience against evolving threats.

Abstract

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.