Detection of PUE Attack in CRN with Reduced Error in Location Estimation Using Novel Bat Algorithm

Detection of PUE Attack in CRN with Reduced Error in Location Estimation Using Novel Bat Algorithm

Aasia Rehman (Kashmir University, Srinagar, India) and Deo Prakash (Shri Mata Vaishno Devi University, Katra, India)
DOI: 10.4018/IJWNBT.2017070101

Abstract

Cognitive Radio Network Technology makes the efficient utilization of scarce spectrum resources by allowing the unlicensed users to opportunistically use the licensed spectrum. Cognitive Radio Network due to its flexible and open nature is vulnerable to a number of security attacks. This paper is mainly concerned with one of the physical layer attack called Primary User Emulation Attack and its detection. This paper solves the problem of PUE attack by localization technique based on TDOA measurements with reduced error in location estimation using a Novel Bat Algorithm (NBA). A number of cooperative secondary users are used for detecting the PUEA by comparing its estimated position with the known position of incumbent. The main goal of NBA is to minimize two fitness functions namely non-linear least square and the maximum likelihood in order to optimize the estimation error. After evaluation, simulation results clearly demonstrates that NBA results in reduced estimation error as compared to Taylor Series Estimation and Particle Swarm Optimization.
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1. Introduction

Today the need for more spectrum bands is increasing rapidly as more wireless applications are being developed. Studies about spectrum have concluded that the licensed spectrum band is most of the time underutilized (Yuan et al., 2012) because of the classical allocation strategies used for spectrum which allocates a large portion of spectrum to licensed devices and at the same time not allowing the unlicensed devices to use the spectrum even though the licensed devices are not fully exploiting the licensed spectrum. Cognitive Radio Technology is an emerging technology that mitigates the issue of spectrum scarcity by allowing the unlicensed devices to exist side by side along with licensed devices. In this new technology the cognitive radio, i.e. unlicensed users opportunistically exploit the white spaces in the licensed spectrum band for communication purposes as long as they do not cause any interference to licensed user i.e. incumbent users, thus ensures the efficient utilization of spectrum. However, if any incumbent activity appears in the channel in which the secondary users are currently operating, they must perform spectrum handoff i.e. move to another vacant band. On the other hand, if other CR user is also transmitting in the same band then self-coexistence techniques are required for sharing the band. Cognitive Radio differs from the traditional radio in the sense that it has the ability of sensing the radio environment and then changes its operating parameters according to the sensed data from the environment. Cognitive Radio Networks are sensitive to various attacks at different layers of OSI model (El-Hajj et al., 2011) as shown in Table 1:

Table 1.
Various Layers and Corresponding Attacks on them
S.no.LayersAttacks
1.Physical LayerPrimaryUser Emulation, Objective Function Attack, Jamming
2.Data Link Layerspectrum sensing data falsification, control channel saturation DoS, selfish channel negotiation
3.Network LayerSink hole attack, Sybil attack, Wormhole attack
4.Transport LayerKey Depletion Attack

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