[Paper Review] Survey of Sybil Attacks in Social Networks

Rupesh Gunturu|arXiv (Cornell University)|Apr 21, 2015

Spam and Phishing Detection42 references16 citations

TL;DR

This survey examines Sybil attacks in social networks, where malicious actors create multiple fake identities to disrupt trust systems, manipulate rankings, or compromise peer-to-peer networks. It reviews defense mechanisms such as reputation systems, graph-based detection, and identity binding, highlighting their strengths and limitations in mitigating Sybil threats across decentralized environments.

ABSTRACT

This paper reviews the Sybil attack in social networks, which has the potential to compromise the whole distributed network. In the Sybil attack, the malicious user claims multiple identities to compromise the network. Sybil attacks can be used to change the overall ranking in voting applications, bad-mouth an opinion, access resources or to break the trust mechanism behind a P2P network. In this paper, different defense mechanisms used to mitigate Sybil attacks are also reviewed.

Motivation & Objective

• To analyze the threat model of Sybil attacks in social networks and their potential to undermine trust and consensus mechanisms.
• To identify the core vulnerabilities in decentralized and peer-to-peer systems that enable Sybil attacks.
• To evaluate existing defense mechanisms against Sybil attacks in terms of scalability, accuracy, and practical deployment.
• To provide a comprehensive overview of detection and prevention techniques for researchers and practitioners.
• To highlight open challenges and future research directions in defending against evolving Sybil attack vectors.

Proposed method

• Systematic review of existing literature on Sybil attacks in social networks and P2P systems.
• Categorization of defense mechanisms into reputation-based, graph-theoretic, and identity-binding approaches.
• Analysis of detection techniques using social network structure, such as clustering and connectivity patterns.
• Evaluation of cryptographic and lightweight solutions for identity binding and proof-of-work to limit fake identity creation.
• Comparison of defense mechanisms based on scalability, resistance to collusion, and resilience to adaptive attackers.
• Incorporation of case studies and real-world applications to illustrate practical deployment challenges.

Experimental results

Research questions

• RQ1 How do Sybil attacks exploit identity proliferation to compromise trust and consensus in social networks?
• RQ2 What are the key architectural and protocol-level weaknesses that enable successful Sybil attacks?
• RQ3 How effective are reputation systems in detecting and mitigating Sybil nodes in dynamic social networks?
• RQ4 What are the trade-offs between detection accuracy, computational cost, and scalability in Sybil defense mechanisms?
• RQ5 What emerging techniques show promise in defending against advanced, adaptive Sybil attacks?

Key findings

• Sybil attacks can severely undermine trust mechanisms in P2P and social networks by enabling a single adversary to control multiple identities.
• Reputation-based systems show promise but are vulnerable to Sybil-controlled colluding nodes that manipulate trust scores.
• Graph-based detection methods, such as analyzing node connectivity and clustering, can identify suspicious identity clusters with moderate accuracy.
• Identity binding techniques, including proof-of-work and hardware-based attestation, reduce the feasibility of creating large numbers of fake identities.
• No single defense mechanism is universally effective; hybrid approaches combining multiple techniques yield better resilience.
• Scalability and resistance to collusion remain major challenges in deploying practical Sybil defense systems in real-world social networks.