Article

The sybil attack in sensor networks: analysis & defenses

Authors:

Adrian PerrigAuthors Info & Claims

IPSN '04: Proceedings of the 3rd international symposium on Information processing in sensor networks

Pages 259 - 268

https://doi.org/10.1145/984622.984660

Published: 26 April 2004 Publication History

Abstract

Security is important for many sensor network applications. A particularly harmful attack against sensor and ad hoc networks is known as the Sybil attack [6], where a node illegitimately claims multiple identities. This paper systematically analyzes the threat posed by the Sybil attack to wireless sensor networks. We demonstrate that the attack can be exceedingly detrimental to many important functions of the sensor network such as routing, resource allocation, misbehavior detection, etc. We establish a classification of different types of the Sybil attack, which enables us to better understand the threats posed by each type, and better design countermeasures against each type. We then propose several novel techniques to defend against the Sybil attack, and analyze their effectiveness quantitatively.

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Cited By

Baird IGhaleb BWadhaj IRussell GBuchanan W(2024)Securing IoT: Mitigating Sybil Flood Attacks with Bloom Filters and Hash ChainsElectronics10.3390/electronics1317346713:17(3467)Online publication date: 31-Aug-2024
https://doi.org/10.3390/electronics13173467
Cárdenas-Haro JSalem MAldaco-Gastélum ALópez-Avitia RDawson M(2024)Enhancing Security in Social Networks through Machine Learning: Detecting and Mitigating Sybil Attacks with SybilSocNetAlgorithms10.3390/a1710044217:10(442)Online publication date: 3-Oct-2024
https://doi.org/10.3390/a17100442
Baird IGhaleb BWadhaj IRussell GBuchanan W(2024)Safeguarding IoT Systems: Novel Authentication Method to Counteract Sybil and Flood AttacksProceedings of the 2024 4th International Conference on Robotics and Control Engineering10.1145/3674746.3674772(165-170)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3674746.3674772
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Index Terms

The sybil attack in sensor networks: analysis & defenses
1. Networks
  1. Network protocols

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Published In

cover image ACM Conferences

IPSN '04: Proceedings of the 3rd international symposium on Information processing in sensor networks

April 2004

464 pages

ISBN:1581138466

DOI:10.1145/984622

Conference Chairs:
Kannan Ramchandran
University of California, Berkeley
,
Janos Sztipanovits
Vanderbilt University
,
Program Chairs:
Jennifer Hou
University of Illinois at Urbana Champaign
,
Thrasyvoulos Pappas
Northwestern University

Copyright © 2004 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 April 2004

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IPSN04: Third International Symposium on Information Processing in Sensor Networks 2004

April 26 - 27, 2004

California, Berkeley, USA

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Overall Acceptance Rate 143 of 593 submissions, 24%

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Cited By

Baird IGhaleb BWadhaj IRussell GBuchanan W(2024)Securing IoT: Mitigating Sybil Flood Attacks with Bloom Filters and Hash ChainsElectronics10.3390/electronics1317346713:17(3467)Online publication date: 31-Aug-2024
https://doi.org/10.3390/electronics13173467
Cárdenas-Haro JSalem MAldaco-Gastélum ALópez-Avitia RDawson M(2024)Enhancing Security in Social Networks through Machine Learning: Detecting and Mitigating Sybil Attacks with SybilSocNetAlgorithms10.3390/a1710044217:10(442)Online publication date: 3-Oct-2024
https://doi.org/10.3390/a17100442
Baird IGhaleb BWadhaj IRussell GBuchanan W(2024)Safeguarding IoT Systems: Novel Authentication Method to Counteract Sybil and Flood AttacksProceedings of the 2024 4th International Conference on Robotics and Control Engineering10.1145/3674746.3674772(165-170)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3674746.3674772
Dogan-Tusha SAlthunibat SQaraqe M(2024)Doppler-Shift-Based Sybil Attack Detection for Mobile IoT NetworksIEEE Internet of Things Journal10.1109/JIOT.2023.328804011:1(1136-1147)Online publication date: 1-Jan-2024
https://doi.org/10.1109/JIOT.2023.3288040
Kumar BBhuyan B(2024)Game Theoretic Defense Framework Against Sybil AttacksSN Computer Science10.1007/s42979-024-03153-05:7Online publication date: 4-Sep-2024
https://dl.acm.org/doi/10.1007/s42979-024-03153-0
Zhao GChen HWang J(2024)An edge-assisted group authentication scheme for the narrowband internet of thingsComplex & Intelligent Systems10.1007/s40747-024-01514-z10:5(6597-6618)Online publication date: 16-Jun-2024
https://doi.org/10.1007/s40747-024-01514-z
Prasad AKapoor PSingh T(2024)Security Threats in IOT and Their PreventionCommunication Technologies and Security Challenges in IoT10.1007/978-981-97-0052-3_7(131-146)Online publication date: 26-Mar-2024
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Wisdom DVincent OIgulu KHyacinth EChristian AOduntan OHauni A(2024)Industrial IoT Security Infrastructures and ThreatsCommunication Technologies and Security Challenges in IoT10.1007/978-981-97-0052-3_19(369-402)Online publication date: 26-Mar-2024
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Michele MJattke PZibung JRazavi K(2024)PayRide: Secure Transport e-Ticketing with Untrusted Smartphone LocationDetection of Intrusions and Malware, and Vulnerability Assessment10.1007/978-3-031-64171-8_14(261-282)Online publication date: 9-Jul-2024
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Saidi A(2024)Attacks and Countermeasures in Wireless Sensor NetworksIoT-Enabled Energy Efficiency Assessment of Renewable Energy Systems and Micro-grids in Smart Cities10.1007/978-3-031-60629-8_4(34-47)Online publication date: 28-May-2024
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