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Cited by 399

The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.

Sybil Attacks and Their Defenses in the Internet of Things

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

Abstract

The emerging Internet-of-Things (IoT) are vulnerable to Sybil attacks where attackers can manipulate fake identities or abuse pseudoidentities to compromise the effectiveness of the IoT and even disseminate spam. In this paper, we survey Sybil attacks and defense schemes in IoT. Specifically, we first define three types Sybil attacks: SA-1, SA-2, and SA-3 according to the Sybil attacker's capabilities. We then present some Sybil defense schemes, including social graph-based Sybil detection (SGSD), behavior classification-based Sybil detection (BCSD), and mobile Sybil detection with the comprehensive comparisons. Finally, we discuss the challenging research issues and future directions for Sybil defense in IoT.

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Metadata

Authors
Zhang, K., Liang, X., Lu, R., & Shen, X.
Venue
IEEE Internet of Things Journal
Published
2014-10
Volume
1
Issue
5
Pages
372-383
ISSN
2327-4662 (ISSN-L)
OpenAlex
W1980035202
Cited by
399
References
8
FWCI
48.08
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Sybil Attacks and Their Defenses in the Internet of Things. https://app.cochat.ai/papers/10.1109/jiot.2014.2344013
The paper
Zhang, K., Liang, X., Lu, R., & Shen, X. (2014). Sybil Attacks and Their Defenses in the Internet of Things. IEEE Internet of Things Journal. https://doi.org/10.1109/jiot.2014.2344013

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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