A mechanism for detecting dishonest recommendation in indirect trust computation

Iltaf, Naima; Ghafoor, Abdul; Zia, Uzman

doi:10.1186/1687-1499-2013-189

Cited by 24 publications

(16 citation statements)

References 25 publications

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“…Initial credibility of service consumer as recommender is set as 0.5. To compute the accuracy of the reputation score, we compared the reputation score computed through our scheme with the average of reputation values provided by non-malicious users and with the scheme presented in [ 39 ].…”

Section: Resultsmentioning

confidence: 99%

“…The control chart method calculates the lower and the upper confidence limits using the average and the standard deviation to filter out the recommendations that are malicious. In [ 39 ] scheme based on dissimilarity measure is presented to detect malicious recommendations. The scheme focuses on declaring the recommenders as malicious whose provided recommendation is distant from the Median value and has a lower frequency of occurrence.…”

Section: Related Workmentioning

confidence: 99%

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Anonymity-preserving Reputation Management System for health sector

et al. 2018

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In health sector, trust is considered important because it indirectly influences the quality of health care through patient satisfaction, adherence and the continuity of its relationship with health care professionals and the promotion of accurate and timely diagnoses. One of the important requirements of TRSs in the health sector is rating secrecy, which mandates that the identification information about the service consumer should be kept secret to prevent any privacy violation. Anonymity and trust are two imperative objectives, and no significant explicit efforts have been made to achieve both of them at the same time. In this paper, we present a framework for solving the problem of reconciling trust with anonymity in the health sector. Our solution comprises Anonymous Reputation Management (ARM) protocol and Context-aware Trustworthiness Assessment (CTA) protocol. ARM protocol ensures that only those service consumers who received a service from a specific service provider provide a recommendation score anonymously with in the specified time limit. The CTA protocol computes the reputation of a user as a service provider and as a recommender. To determine the correctness of the proposed ARM protocol, formal modelling and verification are performed using High Level Petri Nets (HLPN) and Z3 Solver. Our simulation results verify the accuracy of the proposed context-aware trust assessment scheme.

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Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Anonymity-preserving Reputation Management System for health sector

et al. 2018

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“…Firstly, the influence of punishment and regulation mechanism on direct trust value is verified with dynamic change of communication behavior between nodes in our trust model. Then, our model compares with DDR (Detecting Dishonest Recommendation) [29] in terms of trust value under the condition of no attack or malicious node's attack. Subsequently, the comparison of ACOSR, DDR, and SRC (Secure and Robust Clustering) [30] algorithm demonstrates in aspects of the average energy consumption, the average time delay, throughput, and the packet loss rate.…”

Section: Resultsmentioning

confidence: 99%

An emerging intelligent optimization algorithm based on trust sensing model for wireless sensor networks

Wang

Zhang

Shu

2018

J Wireless Com Network

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Due to the limitation of battery power, processing capacity, and storage, the sensor nodes are easy to be captured, destroyed, or attacked in an open environment. As a result, the security and reliability of data transmission cannot be guaranteed. In order to resist the internal attacks from malicious nodes, an ant colony optimization algorithm for secured routing based on trust sensing model (ACOSR) in wireless sensor networks is proposed. Firstly, a reliable evaluation model of trust perception is presented, which can estimate the node's trust value derived from its behavior to identify or isolate the malicious nodes effectively. The penalty function and regulator function are applied to reflect the effect of state changes on the trust value according to the node's behavior in the process of the communication. Secondly, the trust evaluation model is introduced into the ant colony routing algorithm to improve the security for data forwarding. The simulation results show that the proposed algorithm has improved the performance significantly in terms of packet loss rate, end to end delay, throughput, and energy consumption and demonstrates good resistance to black hole attack.

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“…The authors of Dishonest Recommendation Detection Model Ullah et al 13 provided the approach proposed in Iltaf et al 14 with some level of resistance to bad mouthing attacks. To achieve this, recommendations are accepted only when they neither are highly deviated from the mean trust value nor have been received from a low trustworthy node.…”

Section: Related Workmentioning

confidence: 99%

A green trust‐distortion resistant trust management scheme on mobile ad hoc networks

Movahedi

Hosseini

2017

Int J Communication

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Trust management is an emerging security approach used to conduct nodes' relationships in mobile ad hoc networks. It relates to assigning a trust level to each network component based on its cooperative behavior with respect to system goals. Because of its infrastructure-less nature, frequent network dynamics, and severe resource constraints, it is complex to establish trust in such a network. Mainly, trust systems are vulnerable to attacks that make use of inherent properties of the trust model to alter the accuracy of estimated trust levels, referred to as trust-distortion attacks.Because of the contradictory nature of such attacks, their detection can be confusing, complex, and energy-demanding, especially in multiattack environments. To handle such threats, we propose a Green Trust-distortion Resistant Trust Management Scheme, called GTRTMS, which handles different trust-distortion attacks in multiattack environments. The proposed solution self-adapts its trust knowledge monitoring according to the network context to conserve the energy of mobile nodes and reduce the produced CO 2 emissions. Simulation results prove that GTRTMS exhibits significantly better performance than the other counterpart in presence of simultaneous and contradictory different trust-distortion attacks.KEYWORDS mobile ad hoc networks, trust-distortion attacks, trust management Int J Commun Syst. 2017;30:e3331.wileyonlinelibrary.com/journal/dac

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A mechanism for detecting dishonest recommendation in indirect trust computation

Cited by 24 publications

References 25 publications

Anonymity-preserving Reputation Management System for health sector

Anonymity-preserving Reputation Management System for health sector

An emerging intelligent optimization algorithm based on trust sensing model for wireless sensor networks

A green trust‐distortion resistant trust management scheme on mobile ad hoc networks

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