Time Series Analysis for Jamming Attack Detection in Wireless Networks

Maggie Cheng, Yi Ling, Wei Biao Wu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Due to the open nature of wireless communication medium, wireless networks are susceptible to jamming attacks. Jammers interfere with the legitimate nodes by sending strong jamming signals. Legitimate nodes can successfully transmit only between the gaps of the jamming signals. It is therefore very important to detect a jamming attack as soon as it happens in order to effectively take counter measurements. There are various types of jamming attacks, however, the {\it signature} of all jamming attacks is the performance degradation of legitimate nodes. Based on this observation, we develop a detection method using time series analysis approach. We model the network measurements taken over time as time series, and employ a sequential change point detection algorithm to detect the change of state in the time series, which is an indicator of change in the network state. Timely and accurate detection is the first step before further identification and localization of the source of interference. In this paper, we address the detection part and leave the localization of the jammer to future work. The jamming attacks are simulated in ns-3 simulator, and the detection result is satisfactory in terms of false alarm rate and detection delay.

Original languageEnglish (US)
Title of host publication2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-7
Number of pages7
ISBN (Electronic)9781509050192
DOIs
StatePublished - Jul 1 2017
Event2017 IEEE Global Communications Conference, GLOBECOM 2017 - Singapore, Singapore
Duration: Dec 4 2017Dec 8 2017

Publication series

Name2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
Volume2018-January

Other

Other2017 IEEE Global Communications Conference, GLOBECOM 2017
CountrySingapore
CitySingapore
Period12/4/1712/8/17

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

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