Title: Maximum match filtering algorithm to defend spectrum-sensing data falsification attack in CWSN

Authors: Pinaki Sankar Chatterjee; Monideepa Roy

Addresses: Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India ' Kalinga Institute of Industrial Technology, Bhubaneswar 751024, India

Abstract: Cognitive Wireless Sensor Networks (CWSNs) provide better bandwidth utilisation compared to normal Wireless Sensor Networks (WSNs) by using opportunistic spectrum access to transfer data. They transmit data through the primary user's spectrum band when there is heavy traffic in its own network, thereby eliminating collisions and delays in data delivery. During this, CWSNs are subject to several security threats, attacks on secrecy and authentication, attacks on network availability (DOS attacks), stealth attacks on service integrity etc. The Spectrum Sensing Data Falsification (SSDF) attack is a type of DOS attack where the attackers modify the spectrum sensing report to compel the base station to take a wrong collaborative decision regarding the vacant spectrum band in other networks. In this paper, we have proposed the Maximum-Match Filtering algorithm (MMF) for collaborative spectrum sensing and spectrum decision making in CWSNs, which is executed at the base station to counter the SSDF attack.

Keywords: cognitive wireless sensor network; WSN; denial of service attack; spectrum sensing data falsification attack; multiple linear regression.

DOI: 10.1504/IJWMC.2018.095671

International Journal of Wireless and Mobile Computing, 2018 Vol.15 No.2, pp.113 - 122

Received: 24 Feb 2017
Accepted: 26 Mar 2018
Published online: 16 Oct 2018 *

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