Privacy Enhancing Technologies for Wireless Sensor Networks

Chow, Chee W.; Xu, Wenjian; He, Tian

doi:10.1007/978-3-642-40009-4_18

Cited by 4 publications

(4 citation statements)

References 55 publications

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“…Remote sensors need to talk with each other through remote transmission. Remote communications are definitely not hard to be taken after or listened silently by intruder [4].…”

Section: Introductionmentioning

confidence: 99%

Adequate Sparse Secure and Minkowski Distance Based Location Privacy Approach in Wireless Sensor Network

Meena¹,

Sharma²

2017

IJIES

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Abstract:Wireless sensor networks (WSNs) are susceptible to various issues such as privacy and security. To overcome these issues, our worka first validates the location privacy issues and security protection. So that introduce a novel method known as Adequate Sparse Secure and Minkowski distance based Location Privacy (ASSMLP), in this first phase concentrates on location privacy which is improved by presenting a technique known as Fake Source and Fake Sink (FSFS). In this the location of fake node is separated by Modified Pillar k means based Minkowski distance. Second phase deliberate on security and here confidentiality of message can be ensured through sparse matrix. Thus the result shows throughput, energy consumption, energy efficiency, delay and packet delivery ratio and it achieves 2%, 7%, 36%, 8% and 8% better performance than existing work. Clustering accuracy is showed by means of minimum silhouette coefficient. Since real node cannot identify with an intruder.

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“…Remote sensors need to talk with each other through remote transmission. Remote communications are definitely not hard to be taken after or listened silently by intruder [4].…”

Section: Introductionmentioning

confidence: 99%

Adequate Sparse Secure and Minkowski Distance Based Location Privacy Approach in Wireless Sensor Network

Meena¹,

Sharma²

2017

IJIES

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“…Studying existing solutions in similar domains such as wireless sensor networks and MANET shows those approaches cannot be applied directly into the domain of smart home due to producing undesirable extra delay or increasing the energy consumption [8], [9]. Thus, in this paper, we propose a Hybrid Energy-Efficient Privacy Preserving Scheme which is improved version of dummy packet injection approach [10], [11] and a random timing interval generator for determining the transmitting slot. Suggested solution is a decision-making algorithm based on probability theorem and it works by aim of maximizing the confusion level of the attack in its way to discover the correct pattern.…”

Section: Introductionmentioning

confidence: 99%

“…Disastrous results of this type of attacks, such as transferring the data to other parties from criminal organizations to insurance companies or spammers without permission and consent, cannot be avoided because the victim does not know when the attack is happening [13]. Fingerprint and Timing-based Snooping (FATS) is a robust attack to make adversaries able to capture wireless signals emitted from a smart home from somewhere outside of the home and stay undetectable as a nature of any kind of passive attacks [10]. Attackers interfere signals for a while and once the algorithm is trained enough, identities of smart devices and their locations will be clear, afterward, daily activities of residents of the home will be observable for attackers.…”

Section: Introductionmentioning

confidence: 99%

A probability based hybrid energy-efficient privacy preserving scheme to encounter with wireless traffic snooping in smart home

Abrishamchi

Abdullah²,

Cheok

et al. 2017

Proceedings of the SmartCity360 2016

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Application of pervasive computing devices in smart homes are rising sharply and due to this matter, demands for efficient privacy protection are increasing urgently. Possibility of interference in wireless networks is proved by previous work. Adversaries can discover contextual information because of traffic monitoring and classifying transmitters based on their radio fingerprints while data packets are encrypted or content is not important for attackers. To conceal communication patterns various approaches have been investigated. They are mainly based on injection of dummy packets into the network traffic and adding delay to transmission time. In this paper, we introduce a hybrid energy-efficient privacy preserving scheme for generating and sending dummy packets through a decision-making algorithm which works based on probability to maximize confusion of attacker in clarifying the real pattern of network traffic.

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“…In this regard, WSN privacy needs have already been surveyed by several authors. Chow et al [3], Tayebi et al [4], Rios et al [5], Gupta and Chawla [6], Oualha and Olivereau [7], Conti et al [8], Bista and Chang [9], Alemdar and Ersoy [10], or Al Ameen et al [11] are representative examples of systematic literature reviews on the matter. All of them focus on the different techniques that are proposed by authors to address typical security and privacy needs.…”

Section: Introductionmentioning

confidence: 99%

Privacy Models in Wireless Sensor Networks: A Survey

2016

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Wireless Sensor Networks (WSNs) are attracting attention from the research community. One of the key issues is to provide them with privacy protection. In recent years, a huge amount of contributions has been focused on this area. Surveys and literature reviews have also been produced to give a systematic view of the different approaches taken. However, no previous work has focused on privacy models, that is, the set of assumptions made to build the approach. In particular, this paper focuses on this matter by studying 41 papers of the last 5 years. We highlight the great differences appearing among related papers that could make them incompatible to be applied simultaneously. We propose a set of guidelines to build comprehensive privacy models so as to foster their comparability and suitability analysis for different scenarios.

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Privacy Enhancing Technologies for Wireless Sensor Networks

Cited by 4 publications

References 55 publications

Adequate Sparse Secure and Minkowski Distance Based Location Privacy Approach in Wireless Sensor Network

Adequate Sparse Secure and Minkowski Distance Based Location Privacy Approach in Wireless Sensor Network

A probability based hybrid energy-efficient privacy preserving scheme to encounter with wireless traffic snooping in smart home

Privacy Models in Wireless Sensor Networks: A Survey

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