Distributed Two-Step Quantized Fusion Rules Via Consensus Algorithm for Distributed Detection in Wireless Sensor Networks

Nurellari, Edmond; McLernon, Des; Ghogho, Mounir

doi:10.1109/tsipn.2016.2549743

Cited by 40 publications

(33 citation statements)

References 36 publications

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“…Note that in practice we wish to keep P i,f alse d close to zero and P i,true d close to one. Based on this reliability test (i.e., the test in (35)), next we will evaluate the weight combining in (10) such that the probability of detection in (15) is further improved.…”

Section: A Compromised Sns Identificationmentioning

confidence: 99%

See 1 more Smart Citation

A Secure Optimum Distributed Detection Scheme in Under-Attack Wireless Sensor Networks

Nurellari

McLernon

Ghogho

2018

IEEE Trans. on Signal and Inf. Process. over Networks

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Abstract-We address the problem of centralized detection of a binary event in the presence of β fraction falsifiable sensor nodes (SNs) (i.e., controlled by an attacker) for a bandwidthconstrained under − attack spatially uncorrelated distributed wireless sensor network (WSN). The SNs send their one-bit test statistics over orthogonal channels to the fusion center (FC), which linearly combines them to reach to a final decision. Adopting the modified deflection coefficient as an alternative function to be optimized, we first derive in a closed-form the FC optimal weights combining. But as these optimal weights require a − priori knowledge that cannot be attained in practice, this optimal weighted linear FC rule is not implementable. We also derive in a closed-form the expressions for the attacker "flipping probability" (defined in paper) and the minimum fraction of compromised SNs that makes the FC incapable of detecting. Next, based on the insights gained from these expressions, we propose a novel and non-complex reliability-based strategy to identify the compromised SNs and then adapt the weights combining proportional to their assigned reliability metric. In this way, the FC identifies the compromised SNs and decreases their weights in order to reduce their contributions towards its final decision. Finally, simulation results illustrate that the proposed strategy significantly outperforms (in terms of FC's detection capability) the existing compromised SNs identification and mitigation schemes.

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Section: A Compromised Sns Identificationmentioning

confidence: 99%

“…Note that K affects these two metrics through the reliability metric r i (see Fig. 2) in (34) which consequently affects the FC weight combining (37) that finally decides on the FC final test statistic (T f ) (see (10)). …”

Section: A Impact Of the Time Window Length (K) On The Malicious Sn mentioning

confidence: 99%

A Secure Optimum Distributed Detection Scheme in Under-Attack Wireless Sensor Networks

Nurellari

McLernon

Ghogho

2018

IEEE Trans. on Signal and Inf. Process. over Networks

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“…As discussed in the work of Nurellari et al, the performance of the centralised soft CSS can be evaluated for a given P f as

{normalP}_{d}^{smallC} = Q ((), \frac{Q^{- 1} false(P_{f} false) \sqrt{var ((), T_{f}^{SD} true| H_{0})} - double-struckE ((), T_{f}^{SD} true| H_{1}) + double-struckE ((), T_{f}^{SD} true| H_{0})}{\sqrt{var (() T_{f}^{smallSD} | {scriptH}_{1})}}),

where Q (·) is the Gaussian Q ‐function.…”

Section: Cooperative Spectrum Sensingmentioning

confidence: 99%

“…In the work of Soatti et al, a technique named weighted AC accuracy exchange (WAC‐AE) was proposed to solve the localisation problem in networks equipped with several fixed nodes ensuring similar performance to the WAC and optimal ML but with fast convergence. Moreover, in the work of Nurellari et al, a new consensus technique was applied in a quantised way, whereas in the work of Kailkhura et al, a new consensus technique was proposed to deal with security in a cognitive network in a system with Byzantine attacks.…”

Section: Introductionmentioning

confidence: 99%

Improved weighted average consensus in distributed cooperative spectrum sensing networks

Hernandes

Proença

Abrão

2017

Trans Emerging Tel Tech

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This work proposes a fully distributed improved weighted average consensus (IWAC) technique applied to a cooperative spectrum sensing (CSS) problem in cognitive radio systems. This method allows the secondary users to cooperate based on only local information exchange without a fusion centre. We have compared 4 rules of average consensus (AC) algorithms. The first rule is the simple AC without weights. The AC rule presents performance comparable to the traditional CSS techniques such as the equal gain combining rule, which is a soft combining centralised method. Another technique is the weighted AC (WAC) rule, using the weights based on the SUs' channel condition. This technique results in a performance similar to that of the maximum ratio combining with soft combining (centralised CSS). Two new AC rules are analysed, namely, WAC accuracy exchange (WAC‐AE) and IWAC; the former relates the weights to the channel conditions of the SUs' neighbours, whereas the latter combines the conditions of WAC and WAC‐AE in the same rule. All methods are compared with each other and with the hard combining centralised CSS. The WAC‐AE results in a similar performance of the WAC technique but with fast convergence, whereas the IWAC can deliver suitable performance with small complexity increment. Moreover, the IWAC method results in a similar convergence rate than the WAC‐AE method but slightly higher than the AC and WAC methods. Hence, the computational complexity of IWAC, WAC‐AE, and WAC is proven to be very similar. The analyses are based on numerical Monte Carlo simulations, whereas the algorithm's convergence is evaluated for both fixed and dynamic mobile communication scenarios and under additive white Gaussian noise and Rayleigh channels.

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“…Next, in Section IV-B we distinguish again between two different simulation setups but now from the perspective of the FC mechanisms. A. Sub-optimum attacker's strategies Here, we assume that the attacker knows that the FC uses a linear combining strategy but it is not aware of the combining weights used in (11). We also assume that the FC does not act strategically and uses weight combining, without trying to optimize against the behavior of compromised SNs.…”

Section: B Attacker Performance Optimisationmentioning

confidence: 99%

Distributed Binary Event Detection Under Data-Falsification and Energy-Bandwidth Limitation

Nurellari¹,

McLernon²,

Ghogho³

et al. 2016

IEEE Sensors J.

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Abstract-We address the problem of centralized detection of a binary event in the presence of falsifiable sensor nodes (SNs) (i.e., controlled by an attacker) for a bandwidth-constrained under−attack spatially uncorrelated distributed wireless sensor network (WSN). The SNs send their quantized test statistics over orthogonal channels to the fusion center (FC), which linearly combines them to reach a final decision. First (considering that the FC and the attacker do not act strategically), we derive (i) the FC optimal weight combining; (ii) the optimal SN to FC transmit power, and (iii) the test statistic quantization bits that maximize the probability of detection (P d ). We also derive an expression for the attacker strategy that causes the maximum possible FC degradation. But in these expressions, both the optimum FC strategy and the attacker strategy require a − priori knowledge that cannot be obtained in practice. The performance analysis of sub-optimum FC strategies is then characterized, and based on the (compromised) SNs willingness to collaborate, we also derive analytically the sub-optimum attacker strategies. Then, considering that the FC and the attacker now act strategically, we re-cast the problem as a minimax game between the FC and the attacker and prove that the Nash Equilibrium (NE) exists. Finally, we find this NE numerically in the simulation results and this gives insight into the detection performance of the proposed strategies.

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Distributed Two-Step Quantized Fusion Rules Via Consensus Algorithm for Distributed Detection in Wireless Sensor Networks

Cited by 40 publications

References 36 publications

A Secure Optimum Distributed Detection Scheme in Under-Attack Wireless Sensor Networks

A Secure Optimum Distributed Detection Scheme in Under-Attack Wireless Sensor Networks

Improved weighted average consensus in distributed cooperative spectrum sensing networks

Distributed Binary Event Detection Under Data-Falsification and Energy-Bandwidth Limitation

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