Audio Sensing Aid based Wireless Microphone Emulation Attacks Detection

Wang Shan-shan, Luo Xing-guo, Li Bai-nan

Abstract


The wireless microphone network is an important PU network for CRN, but there is no effective technology to solve the problem of microphone evaluation attacks. Therefore, this paper propose ASA algorithm, which utilizes three devices to detect MUs, and they are loudspeaker audio sensor (LAS), environment audio sensor (EAS), and radio frequency fingerprint detector (RFFD). LASs are installed near loudspeakers, which have two main effects: One is to sense loudspeakers’ output, and the other is to broadcast warning information to all SUs through the common control channel when detecting valid output. EASs are pocket voice captures provided to SU, and utilized to sense loudspeaker sound at SU’s location. Utilizing EASs and energy detections in SU can detect primary user emulation attack (PUEA) fast. But to acquire the information of attacked channels, we need explore RFFDs to analyze the features of PU transmitters. The results show that the proposed algorithm can detect PUEA well.

 

DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3424

 


Keywords


Cognition Radio Networks (CRN); Spectrum Sensing; Communication Performance; Secondary User; Primary User Emulation Attack (PUEA)

Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics