Title :
Sybil Attacks and Their Defenses in the Internet of Things
Author :
Kuan Zhang ; Xiaohui Liang ; Rongxing Lu ; Xuemin Shen
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Waterloo, Waterloo, ON, Canada
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.
Keywords :
Internet of Things; computer network security; graph theory; mobile computing; pattern classification; BCSD; Internet-of-Things; IoT; SA-1 Sybil attacks; SA-2 Sybil attacks; SA-3 Sybil attacks; SGSD; Sybil attacker capabilities; Sybil defense schemes; abuse pseudoidentities; behavior classification-based Sybil detection; defense schemes; fake identities; mobile Sybil detection; social graph-based Sybil detection; Computer security; Mobile communication; Mobile computing; Network security; Social network services; Ubiquitous computing; Behavior classification; Internet of Things (IoT); Sybil attack; mobile social network; social network;
Journal_Title :
Internet of Things Journal, IEEE
DOI :
10.1109/JIOT.2014.2344013
