Sybil Attacks and Their Defenses in the Internet of Things

By Kuan Zhang, Xiaohui Liang, Rongxing Lu, Xuemin Shen. IEEE Internet of Things Journal, 2014

376 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/63d4b944582e8dbe08b3f7d06202d644c84b268e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Wei Yu
2. Jairo Gutiérrez
3. Nan Zhang
4. Wei Zhao
5. Khaled Hamed Salah
6. Hanlin Zhang
7. Xinyu Yang
8. Sayan Kumar Ray

In Information Systems

1. Wei Yu
2. Nan Zhang
3. Wei Zhao
4. Khaled Hamed Salah
5. Hanlin Zhang
6. Xinyu Yang
7. Jie Lin

In Signal Processing

1. Wei Yu
2. Khaled Hamed Salah

Citations in the corpus

• Physical-Layer Security in the Internet of Things: Sensing and Communication Confidentiality Under Resource Constraints (2015, neutral): “[16] K.”
• Secure routing for internet of things: A survey (2016, background): “Sinkhole Confidentiality & Integrity attack Compromising huge traffic passing through attacker node IDS solution [60], Parent fail-over, rank authentication technique [64] Hello flooding Availability attack Dissipation of sensor battery power RPL’s global and local repair mechanism removes attack Wo”
• IoT security: Review, blockchain solutions, and open challenges (2017, background): “The communication by Sybil nodes using fake identities in a network may result in spamming, disseminating malware or launching phishing attacks [46,47].”
• A Survey on Internet of Things: Architecture, Enabling Technologies, Security and Privacy, and Applications (2017, methodology): “…and ensure the identifying information and IP addresses not to be leaked to the adversary are possible techniques to be used. g) Sybil attacks: In a sybil attack, a malicious device, namely a sybil device, can claim several legitimate identities and impersonate them in IoT systems [8], [95], [158].”
• A Survey of Internet of Things (IoT) Authentication Schemes (2019, background): “With the presence of a sybil node, the whole system might generate wrong data or even the neighbor nodes will receive spam data and will mislay their privacy [39,40].”
• A Survey on Metaverse: Fundamentals, Security, and Privacy (2022, background): “Sybil adversaries may manipulate multiple faked/stolen identities to gain disproportionately large influence [47] on metaverse services (e.”
• Physical-Layer Security of 5G Wireless Networks for IoT: Challenges and Opportunities (2019, neutral): “receive spam and lose their privacy [39].”