An Access Control for IoT Based on Network Community Perception and Social Trust Against Sybil Attacks

TL;DR

This paper proposes ELECTRON, a social trust-based access control mechanism for IoT networks that effectively detects Sybil attacks by grouping devices into communities based on social similarity, achieving over 90% detection accuracy.

Contribution

The paper introduces ELECTRON, a novel social trust-based access control system for IoT that enhances security against Sybil attacks by leveraging community detection and trust evaluation.

Findings

ELECTRON detects over 90% of Sybil attackers in various IoT community scenarios.

The system achieves 90-95% accuracy with false positive rates near zero.

Simulations demonstrate ELECTRON's effectiveness in protecting IoT networks from intrusions.

Abstract

The evolution of the Internet of Things (IoT) has increased the connection of personal devices, mainly taking into account the habits and behavior of their owners. These environments demand access control mechanisms to protect them against intruders, like Sybil attacks. that can compromise data privacy or disrupt the network operation. The Social IoT paradigm enables access control systems to aggregate community context and sociability information from devices to enhance robustness and security. This work introduces the ELECTRON mechanism to control access in IoT networks based on social trust between devices to protect the network from Sybil attackers. ELECTRON groups IoT devices into communities by their social similarity and evaluates their social trust, strengthening the reliability between legitimate devices and their resilience against the interaction of Sybil attackers. NS-3 Simulations show the ELECTRON performance under Sybil attacks on several IoT communities so that it has gotten to detect more than 90% of attackers in a scenario with 150 nodes into offices, schools, gyms, and~parks communities, and in other scenarios for same communities it achieved around of 90\% of detection. Furthermore, it provided high accuracy, over 90-95%, and false positive rates closer to zero.