Blockchain-enabled identity management for IoT: a multi-layered defense against adversarial AI.

Area of Science:

• Cybersecurity
• Computer Science
• Cryptography

Background:

• The increasing deployment of Internet of Things (IoT) devices, particularly in critical infrastructure, necessitates robust and scalable identity management systems.
• Existing centralized identity systems are vulnerable to sophisticated Artificial Intelligence (AI)-based attacks, including generative spoofing and deepfakes, posing significant security risks.

Purpose of the Study:

• To propose a novel blockchain-based IoT security system that addresses the limitations of centralized approaches.
• To enhance the resilience of IoT identity systems against AI-driven adversarial techniques.
• To ensure privacy-preserving device registration and verification within the IoT ecosystem.

Main Methods:

• Implementation of a decentralized identity verification architecture.
• Integration of zero-knowledge proofs (ZKPs) for privacy-preserving authentication.
• Utilization of Byzantine-resistant federated learning for secure model training.
• Application of formal verification techniques for smart contract security.
• Adversarial simulation, symbolic execution, and threshold cryptography for robust defense.

Main Results:

• Demonstrated significant improvements over existing frameworks, including a 48% reduction in false acceptance rate against Generative Adversarial Network (GAN)-based spoofing.
• Achieved speedup in zero-knowledge proof (ZKP) verification processes.
• Eliminated single points of trust and provided defense against AI-driven attacks through formally modeled state transitions.

Conclusions:

• The proposed blockchain-enabled identity management system offers a robust solution for securing IoT environments against AI-based threats.
• The system effectively balances performance and security, providing a scalable and privacy-preserving approach to IoT identity verification.
• This research contributes a novel framework for enhancing the trustworthiness and resilience of critical IoT infrastructure.