Enhanced Beta Trust Model in wireless sensor networks

Umarani, V.; Sundaram, K. Soma; Jayashree, D.

doi:10.1109/icices.2016.7518888

Cited by 10 publications

(7 citation statements)

References 12 publications

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“…However, it costs a lot of energy and increases the time complexity. Umarani [39] established an enhanced beta trust model to find a malicious attack. The neighbor node is selected by the sensor node based on trust information in the course of communication.…”

Section: Related Workmentioning

confidence: 99%

An Effective Exponential-Based Trust and Reputation Evaluation System in Wireless Sensor Networks

2019

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Wireless sensor networks (WSNs) are vulnerable to many security threats from compromised nodes, and because the WSNs are resource-constrained, the traditional security methods cannot be used to resist the internal attacks from compromised nodes. The trust and reputation evaluation system is the most effective security mechanisms to protect WSNs from internal attacks. The exponential-based trust and reputation evaluation system (ETRES) is proposed for WSNs' node trust and reputation evaluation. ETRES is used to observe the nodes' behavior, and exponential distribution is applied to represent the distribution of nodes' trust. The trust of the node is used to look for reliable nodes to transmit data and weaken malicious attacks within the wireless sensor networks. More significantly, the entropy theory is used to measure the uncertainty of direct trust values in this paper. Indirect trust is introduced to strengthen interaction information when the uncertainty of direct trust is enough high. It can not only reduce the computing power of nodes but also prolong the lifetime of the network. In addition, the confidence factor is redefined, which can dynamically adjust the node trust value to weaken the harmful effects of the compromised nodes. The simulation results show that the proposed system can more effectively defend the internal attack than the beta-based trust and reputation evaluation system (RFSN) and the binomial-based trust management System (BTMS). The proposed method can be used to strengthen network security by selecting reliable nodes. What is more, the information trust and energy are prone to integrate into ETRES.

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Section: Related Workmentioning

confidence: 99%

An Effective Exponential-Based Trust and Reputation Evaluation System in Wireless Sensor Networks

2019

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“…But among the related literatures, some merely use the required components while ignoring the others as an integral part of the whole. For example, regarding the reputation fusion, some literatures such as [21,24,26,29,35,36] use both direct reputation and indirect reputation, while others like [30,31,33,41,42,43] only apply direct reputation. For another example, as is shown in Table 1, on the reputation aging, among the literatures that apply direct reputation and/or indirect reputation, only a few of them such as [21,24,25,33] use the reputation aging, while other literatures ignore it for no reason.…”

Section: Reputation Agingmentioning

confidence: 99%

“…For another example, as is shown in Table 1, on the reputation aging, among the literatures that apply direct reputation and/or indirect reputation, only a few of them such as [21,24,25,33] use the reputation aging, while other literatures ignore it for no reason. Besides, by using the concept of binomial reputation, energy reputation [36,37], communication reputation [25,34,35,36,37], and data reputation like [30,34,41,42,59] and so on are introduced so as to save individual node energy and ensure the reliable communication and data transmission. Further, penalty and reward mechanisms [43], light computational complexity such as [21,24,26,27], and energy issues like [43,44,76] and so on are also considered in order to stimulate node cooperation, avoid running complex algorithms, and balance the energy consumed in the network.…”

Section: Reputation Agingmentioning

confidence: 99%

Binomial Distribution Based Reputation for WSNs: A Comprehensive Survey

2021

KSII TIIS

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“…Up to now, many trust models are proposed [14][15][16][17][18][19][20] to observe node behaviors and resist internal attacks from compromised nodes. Some typical works are discussed as follows.…”

Section: Related Workmentioning

confidence: 99%

PDTM: Poisson Distribution-based Trust Model for Web of Things

Fang

Zhang

Chen

et al. 2021

Companion Proceedings of the Web Conference 2021

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Web of things (WoT) are inclined to suffer from internal attacks, which are from compromised nodes. Due to resource-constraint of WoT, the traditional security methods cannot be deployed. One of the most appropriate protection mechanisms to resist internal attacks is the trust management system. For the sake of evaluate the performance of WoT reasonably and appropriately, we improve the Beta-based reputation system, and propose a Poisson Distributionbased trust model (PDTM) in this paper. In view of evaluating a sensor node (or terminal) behaviors, its reputation and trust are represented by the Poisson distribution. PDTM is used to look for reliable nodes to transmit data and weaken malicious attacks within WoTs. The simulation results indicate that the PDTM can resist internal attack effectively, in order to strengthen the network security.

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Enhanced Beta Trust Model in wireless sensor networks

Cited by 10 publications

References 12 publications

An Effective Exponential-Based Trust and Reputation Evaluation System in Wireless Sensor Networks

An Effective Exponential-Based Trust and Reputation Evaluation System in Wireless Sensor Networks

Binomial Distribution Based Reputation for WSNs: A Comprehensive Survey

PDTM: Poisson Distribution-based Trust Model for Web of Things

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