Robustness of Trust and Reputation Systems: Does It Matter?

Jøsang, Audun

doi:10.1007/978-3-642-29852-3_21

Cited by 48 publications

(44 citation statements)

References 20 publications

(18 reference statements)

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“…3.1. We first conduct a formalized threat analysis, based on the approach in [2], to show where potential attack vectors could appear in the system and which security and privacy requirements they target at. In a second step, we show how our protocol faces these potential attacks.…”

Section: Evaluation and Discussionmentioning

confidence: 99%

Privacy-preserving reputation management

Petrlic

Lutters

Sorge

2014

Proceedings of the 29th Annual ACM Symposium on Applied Computing

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Reputation systems provide reputation values of rated parties to users. These reputation values, typically aggregations of individual user ratings, shall be reliable, i.e. should enable a realistic assessment of the probability that the rated party behaves as expected in a transaction. In order for the reputation values to stay reliable and, thus, for the reputation system to provide a benefit, the system needs to be resistant against manipulations by users, the rated parties trying to improve their reputation values, and even against competitors trying to worsen a reputation value. At the same time, a reputation system shall provide privacy protection for users: rated parties shall not be able to learn who provided a certain rating. Otherwise users might not take part in the system as they fear bad feedback in revenge for bad ratings, or users do not want to be connected to certain transactions based on their provided ratings.In this paper we come up with a solution that provides both, reliability of reputation values on the one hand, and privacy protection for users on the other hand. In contrast to related work, our solution only makes use of a single reputation provider that needs to be trusted (to a certain extent) and does not require any bulletin boards to be present in the system. We make use of the Paillier cryptosystem to provide an aggregation of individual user ratings in a way that no party can learn which user provided a certain rating.

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Section: Evaluation and Discussionmentioning

confidence: 99%

Privacy-preserving reputation management

Petrlic

Lutters

Sorge

2014

Proceedings of the 29th Annual ACM Symposium on Applied Computing

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show abstract

“…For an overview of attacks on trust and reputation management systems, see, e.g. [29]. Specific countermeasures are often system-or domainspecific, such as those presented for mobile ad-hoc networks in [30] or electronic markets in [31].…”

Section: Properties Of Trustmentioning

confidence: 99%

The Social Concept of Trust as Enabler for Robustness in Open Self-Organising Systems

Anders

Seebach

Steghöfer

et al. 2016

Trustworthy Open Self-Organising Systems

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The participants in open self-organising systems, including users and autonomous agents, operate in a highly uncertain environment in which the agents' benevolence cannot be assumed. One way to address this challenge is to use computational trust. By extending the notion of trust as a qualifier of relationships between agents and incorporating trust into the agents' decisions, they can cope with uncertainties stemming from unintentional as well as intentional misbehaviour. As a consequence, the system's robustness and efficiency increases. In this context, we show how an extended notion of trust can be used in the formation of system structures, algorithmically to mitigate uncertainties in task and resource allocation, and as a sanctioning and incentive mechanism. Beyond that, we outline how the

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“…Paper [23] discussed the impact of robustness against strategic manipulation for the usefulness of trust and reputation systems in general. Paper [31] proposed a computational trust model similar to real-life stereotypes.…”

Section: Review Mining For Computing Reputation and Trustmentioning

confidence: 99%

Reputation Systems: Evaluating Reputation Among All Good Sellers

Jha

Ramu

Shenoy

et al. 2017

Data-Enabled Discov. Appl.

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A reputation system assists people selecting whom to trust, encourages trustworthy action, and discourages participation of unskilled or dishonest. The "all good reputation" problem is common in current reputation systems, especially in e-commerce domain, making it difficult for buyers to choose credible sellers. Observing high growth of online data in Hindi language, in this paper, we propose a reputation system in this language. The functions of this system include (1) review mining for different criteria of online transactions, (2) calculation of reputation rating using Bayesian method, (3) calculation of reputation weight using typed dependency relation representation and Latent Dirichlet Allocation topic modeling technique for each criteria from user reviews, and (4) ranking sellers based on computed reputation score. Extensive simulations conducted on eBay dataset and TripAdvisor dataset show its effectiveness in solving "all good reputation" problem. So far, as our knowledge is concerned, this is the first work in Hindi language on reputation system. Keywords E-commerce · Hindi · Natural language processing · Reputation system · Review mining Highlights -The proposed Reputation System is a solution to "all good reputation" problem in e-commerce domain.Vandana Jha vjvandanajha@gmail.com 1 Department of Computer Science and Engineering, University Visvesvaraya College of Engineering, Bangalore University, Bangalore, India -Our system is implemented on Hindi language Product reviews and Hotel reviews. It can be easily extended to any reviews in e-commerce domain by using language specific parser and tagger. -Several experiments have been performed and the results obtained are more accurate in ranking the sellers. -Our system is compared with existing system for ranking the sellers. The sellers which were at the same rank using existing system, can be accurately ranked at different levels using our approach.

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Robustness of Trust and Reputation Systems: Does It Matter?

Cited by 48 publications

References 20 publications

Privacy-preserving reputation management

Privacy-preserving reputation management

The Social Concept of Trust as Enabler for Robustness in Open Self-Organising Systems

Reputation Systems: Evaluating Reputation Among All Good Sellers

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