Sybil Attacks and Defenses in Internet of Things and Mobile Social Networks

Abstract

Sybil attacks present a unique threat in the context of Mobile Social<br> Networks and the Internet of Things. Existing research activity in this<br> field focuses on developing novel detection techniques or improving<br> existing ones, but there is a paucity of knowledge about the current<br> types of Sybil attacks and their countermeasures. The purpose of this<br> paper is to explore the different types of Sybil attacks and potential<br> countermeasures. An extensive literature review is conducted to<br> analyze Sybil attacks and classify the defense methods and techniques.<br> The findings show that the common Sybil attacks in MSN and IoT can<br> be categorized into three orthogonal dimensions that represent distinct<br> attack characteristics: direct and indirect communication attacks;<br> fabricated and stolen identity attacks; and simultaneous and nonsimultaneous<br> attacks. In Wireless Sensor Networks (WSNs), Sybil<br> attacks can be categorized further into four types depending on the<br> protocols that they target: routing attacks, distribution storage attacks,<br> data aggregation attacks, and resource allocation attacks. The defense<br> mechanisms fall into four broad categories: graph-based methods,<br> Machine Learning techniques, prevention methods, and manual<br> verification methods.