Scalable PHY-Layer Security for Distributed Detection in Wireless Sensor Networks

Soosahabi, Reza; Naraghi-Pour, Mort

doi:10.1109/vtcfall.2012.6399340

Cited by 11 publications

(19 citation statements)

References 22 publications

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“…The study of Soosahabi et al; [13] presented a cryptographic probabilistic approach to the deliberately present state of transmission whether it could be a harmless or harmful state.…”

Section: Techniques On Cryptography Based Securitymentioning

confidence: 99%

Balancing Trade-off between Data Security and Energy Model for Wireless Sensor Network

Manjunath¹,

Rao²

2018

IJECE

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An extensive effort to evolve various routing protocol to ensure optimal data delivery in energy efficient way is beneficial only if there is additional means of security process is synchronized. However, the security process consideration introduces additional overhead thus a security mechanism is needed to accomplish an optimal trade-off that exists in-between security as well as resource utilization especially energy. The prime purpose of this paper is to develop a process of security in the context of wireless sensor networks (WSN) by introducing two types of sensor node deployed with different capabilities. The proposed algorithm Novel Model of Secure Paradigm (N-MSP) which is further integrated with WSN. However, this algorithm uses a Hash-based Message Authentication Code (HMAC) authentication followed by pairwise key establishment during data aggregation process in a WSN. The extensive simulation carried out in a numerical platform called MATLAB that depicts that the proposed N-MSP achieves optimal processing time along with energy efficient pairwise key establishment during data aggregation process. Keyword:HMAC Pair-wise key establishment Security WSN Copyright © 2018 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Manjunath B. E., Dept. of ECE, Jain University, Bangalore, India. Email: manjunathbephd@gmail.com INTRODUCTIONA WSN is formed with sensor nodes (SNs) using ad-hoc technology. Due to ad hoc technology, SNs are self-configured and operates the data transfer without any access points as well the computing takes place in a distributed manner. Traditionally, there exist many communication protocols such as Direct Communication (DC), Minimum transmission energy (MTE) protocol like hop-by-hop. The problem found in DC is the remote node from the sink die soon and is reserves in MTE, where nearby node die soon. A hierarchal routing mechanism, where the entire network is divided into groups called clusters, and a local sink in each cluster is elected which is called as a cluster head (CH) or aggregator node.In initial cluster-based protocols, the cluster was static, which provides inconsistency of energy use because of the successive election of the same node as CH. The limitation of the static cluster is overcome in a state of artwork LEACH [1], wherein every communication cycle a new set of the cluster is formed and CH election. Since LEACH, enormous efforts are made by various other researchers towards developing new protocols for routing or communication, the collective information can be found in [2]. The WSNs having exploding usage into different critical applications since its conceptualization on the timeline, and the few to name includes (a) smart farming, (b) structural health monitoring, (c) fire detection in forest, (d) traffic congestion, etc. till Internet of Things (IoT) application so it is not just limited to military applications rather it has become a lifeline. The threats of attacks on this network are distinct philosophical to any network

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“…The study of Soosahabi et al; [13] presented a cryptographic probabilistic approach to the deliberately present state of transmission whether it could be a harmless or harmful state.…”

Section: Techniques On Cryptography Based Securitymentioning

confidence: 99%

Balancing Trade-off between Data Security and Energy Model for Wireless Sensor Network

Manjunath¹,

Rao²

2018

IJECE

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“…Here, f γs,e is the derivative of F γs,e given in (6), and f γap,e is the derivative of F γap,e given in (8).…”

Section: Overall Average Secrecy Ratementioning

confidence: 99%

“…The core idea behind it is to exploit the characteristics of wireless channels such as fading or noise to transmit a message from a source to an intended destination while keeping the message confidential from eavesdroppers [4,5]. Physical layer security schemes have been recently proposed for WSNs to combat eavesdropping [6][7][8][9]. In [6], the downlink secure transmission from the mobile agent to the authorized user was considered and perfect secrecy can be achieved by intentionally creating channel variation.…”

Section: Introductionmentioning

confidence: 99%

“…In [7], a detection problem under physical layer secrecy constraints in an energy-constrained WSNs was addressed, and the optimal operative solutions were analyzed. In [8], sensor transmissions were observed by the authorized fusion center (FC) and unauthorized (third party) FC. It was shown that physical layer security for distributed detection is scalable due to its low computational complexity.…”

Section: Introductionmentioning

confidence: 99%

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Secure Multi-Antenna Transmission in Three-Tier Wireless Sensor Networks

Deng¹,

Wang²,

Elkashlan³

et al. 2014

2015 IEEE Global Communications Conference (GLOBECOM)

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This paper develops a tractable framework for exploiting the potential benefits of physical layer security in threetier wireless sensor networks. In such networks, the sensing data from the remote sensors are collected by sinks with the help of access points, and the external eavesdroppers intercept the data transmissions. We adopt the stochastic geometry approach to model the random locations and spatial densities of the sensors, access points, sinks, and eavesdroppers. We focus on the secure transmission in two scenarios: i) the active sensors transmit their sensing data to the access points, and ii) the active access points forward the data to the sinks. We derive new compact expressions for the overall average secrecy rate in such networks. Numerical results corroborate our analysis and show that multiple-antenna technique at the access points can enhance the security. Our results show that the overall average secrecy rate first increases with increasing the number of access points, and there exists a critical value beyond which the overall average secrecy rate decreases with increasing the number of access points. When adding the number of active sensors, the overall average secrecy rate decreases. In contrast, increasing the number of sinks improves the overall average secrecy rate.

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“…Voting rules or q-out-of-L rules [2] are commonly employed in the FC to detect the occurrence of an event in decentralized sensing [10], [11], [26], [29], [30]. Based on this rule, the detected hypothesis is H 1 if at least q out of L nodes vote in favor of this event.…”

Section: B Reputation-based Node Classifiermentioning

confidence: 99%

Decentralized Hypothesis Testing in Wireless Sensor Networks in the Presence of Misbehaving Nodes

Soltanmohammadi

Orooji

Naraghi-Pour

2013

IEEE Trans.Inform.Forensic Secur.

Self Cite

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Abstract-Wireless sensor networks are prone to node misbehavior arising from tampering by an adversary (Byzantine attack), or due to other factors such as node failure resulting from hardware or software degradation. In this paper we consider the problem of decentralized detection in wireless sensor networks in the presence of one or more classes of misbehaving nodes. Binary hypothesis testing is considered where the honest nodes transmit their binary decisions to the fusion center (FC), while the misbehaving nodes transmit fictitious messages. The goal of the FC is to identify the misbehaving nodes and to detect the state of nature. We identify each class of nodes with an operating point (false alarm and detection probabilities) on the ROC (receiver operating characteristic) curve. Maximum likelihood estimation of the nodes' operating points is then formulated and solved using the expectation maximization (EM) algorithm with the nodes' identities as latent variables. The solution from the EM algorithm is then used to classify the nodes and to solve the decentralized hypothesis testing problem. Numerical results compared with those from the reputation-based schemes show a significant improvement in both classification of the nodes and hypothesis testing results. We also discuss an inherent ambiguity in the node classification problem which can be resolved if the honest nodes are in majority.

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Scalable PHY-Layer Security for Distributed Detection in Wireless Sensor Networks

Cited by 11 publications

References 22 publications

Balancing Trade-off between Data Security and Energy Model for Wireless Sensor Network

Balancing Trade-off between Data Security and Energy Model for Wireless Sensor Network

Secure Multi-Antenna Transmission in Three-Tier Wireless Sensor Networks

Decentralized Hypothesis Testing in Wireless Sensor Networks in the Presence of Misbehaving Nodes

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