Localization in Wireless Sensor Networks: Byzantines and Mitigation Techniques

Vempaty, Aditya; Özdemir, Onur; Agrawal, K.; Chen, Hao; Varshney, Pramod K.

doi:10.1109/tsp.2012.2236325

Cited by 96 publications

(69 citation statements)

References 24 publications

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“…In practice, where T is finite, it is intractable to determine the conditional distribution of Λ i , which is necessary to come up with the optimal choice of η. Therefore, in this paper, we assume that T → ∞ and present an asymptotic choice of the tagging threshold η used in Equation (24).…”

Section: B Optimal Choice Of the Tagging Threshold As T → ∞mentioning

confidence: 99%

“…Distributed target localization in the presence of Byzantine attacks was addressed by Vempaty et al in [24], where the sensors quantize their observations into binary decisions, which are transmitted to the FC. Similar to Rawat et al 's approach in [20], the authors in [24] investigated the problem of distributed target localization from both the network's and Byzantine attacker's perspectives, first by identifying the optimal Byzantine attack and second, mitigating the impact of the attack with the use of non-identical quantizers at the sensors.…”

Section: Introductionmentioning

confidence: 99%

“…Similar to Rawat et al 's approach in [20], the authors in [24] investigated the problem of distributed target localization from both the network's and Byzantine attacker's perspectives, first by identifying the optimal Byzantine attack and second, mitigating the impact of the attack with the use of non-identical quantizers at the sensors.…”

Section: Introductionmentioning

confidence: 99%

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Distributed Inference With M-Ary Quantized Data in the Presence of Byzantine Attacks

Nadendla

Han

Varshney

2014

IEEE Trans. Signal Process.

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Abstract-The problem of distributed inference with M-ary quantized data at the sensors is investigated in the presence of Byzantine attacks. We assume that the attacker does not have knowledge about either the true state of the phenomenon of interest, or the quantization thresholds used at the sensors. Therefore, the Byzantine nodes attack the inference network by modifying modifying the symbol corresponding to the quantized data to one of the other M symbols in the quantization alphabetset and transmitting the false symbol to the fusion center (FC). In this paper, we find the optimal Byzantine attack that blinds any distributed inference network. As the quantization alphabet size increases, a tremendous improvement in the security performance of the distributed inference network is observed.We also investigate the problem of distributed inference in the presence of resource-constrained Byzantine attacks. In particular, we focus our attention on two problems: distributed detection and distributed estimation, when the Byzantine attacker employs a highly-symmetric attack. For both the problems, we find the optimal attack strategies employed by the attacker to maximally degrade the performance of the inference network. A reputationbased scheme for identifying malicious nodes is also presented as the network's strategy to mitigate the impact of Byzantine threats on the inference performance of the distributed sensor network.

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Section: B Optimal Choice Of the Tagging Threshold As T → ∞mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Distributed Inference With M-Ary Quantized Data in the Presence of Byzantine Attacks

Nadendla

Han

Varshney

2014

IEEE Trans. Signal Process.

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“…Here, a reputation-based scheme is proposed for identifying the compromised SNs by accumulating the deviations between each SN and the FC decision over a time window duration. The authors in [27] also consider binary Byzantine attacks, in the context of target localization, where the SNs transmit their binary decisions to the FC. These authors also propose two techniques to mitigate the negative input of the compromised SNs on the FC decision.…”

Section: Introductionmentioning

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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“…Over the course of the past decade, there have been a large number of researches on localization for WSNs [2][3][4][5][6][7][8]. They share the same main idea that nodes with unknown coordinates are utilized by one or more GPS-equipped nodes with known coordinates in order to estimate their positions.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Node Localization Approach with RSSI for Randomly Deployed Wireless Sensor Networks

Zhang

Fang

Meng

2016

Journal of Electrical and Computer Engineering

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An efficient path planning approach in mobile beacon localization for the randomly deployed wireless sensor nodes is proposed in this paper. Firstly, in order to improve localization accuracy, the weighting function based on the distance between nodes is constructed. Moreover, an iterative multilateration algorithm is also presented to avoid decreasing the localization accuracy. Furthermore, a path planning algorithm based on grid scan which can traverse entirely in sensor field is described. At the same time, the start conditions of localization algorithm are also proposed to improve localization accuracy. To evaluate the proposed path planning algorithm, the localization results of beacon nodes randomly deployed in sensor field are also provided. The proposed approach can provide the deployment uniformly of virtual beacon nodes among the sensor fields and the lower computational complexity of path planning compared with method which utilizes only mobile beacons on the basis of a random movement. The performance evaluation shows that the proposed approach can reduce the beacon movement distance and the number of virtual mobile beacon nodes by comparison with other methods.

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Localization in Wireless Sensor Networks: Byzantines and Mitigation Techniques

Cited by 96 publications

References 24 publications

Distributed Inference With M-Ary Quantized Data in the Presence of Byzantine Attacks

Distributed Inference With M-Ary Quantized Data in the Presence of Byzantine Attacks

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

An Efficient Node Localization Approach with RSSI for Randomly Deployed Wireless Sensor Networks

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