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

Volume

1

Issue

5

fYear

2014

fDate

Oct. 2014

Firstpage

372

Lastpage

383

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;

fLanguage

English

Journal_Title

Internet of Things Journal, IEEE

Publisher

ieee

ISSN

2327-4662

Type

jour

DOI

10.1109/JIOT.2014.2344013

Filename

6868197