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

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