Optimal Trust Network Analysis with Subjective Logic

Jøsang, Audun; Bhuiyan, Touhid

doi:10.1109/securware.2008.64

Cited by 237 publications

(318 citation statements)

References 5 publications

Supporting

Mentioning

302

Contrasting

Unclassified

Order By: Relevance

“…This makes the derived stereotypes easy to be interpreted by the real users. Similarly to our Stereotype-Sharing Overlay Network, in their work, new trustors can request stereotypes from the experienced ones, and then combine these stereotypes with the target agent's reputation (if any) using subjective logic [15]. Although similar, our approach has several advantages: (1) as a basic trust model, StereoTrust uses the (well adapted) beta distribution to derive stereotypes and trust, thus the resulting decision is easy to be interpreted; (2) The work [7] shares agents' local stereotypes heuristically (e.g., no discussion on how stereotype providers are selected) while StereoTrust offers a more sophisticated sharing mechanism by maintaining a dedicated overlay network for exchanging, combining, and updating stereotypes; (3) StereoTrust is applicable in practice as demonstrated in real-world dataset (Epinions.com) based evaluation (see Section 8) presented in this paper, as well as in other diverse applications and settings in which we have applied stereotype to derive trust [22,25].…”

Section: Related Workmentioning

confidence: 99%

Trust beyond reputation: A computational trust model based on stereotypes

Liu

Datta

Rządca

2013

Electronic Commerce Research and Applications

View full text Add to dashboard Cite

Models of computational trust support users in taking decisions. They are commonly used to guide users' judgements in online auction sites; or to determine quality of contributions in Web 2.0 sites. However, most existing systems require historical information about the past behavior of the specific agent being judged. In contrast, in real life, to anticipate and to predict a stranger's actions in absence of the knowledge of such behavioral history, we often use our "instinct"-essentially stereotypes developed from our past interactions with other "similar" persons. In this paper, we propose StereoTrust, a computational trust model inspired by stereotypes as used in real-life. A stereotype contains certain features of agents and an expected outcome of the transaction. When facing a stranger, an agent derives its trust by aggregating stereotypes matching the stranger's profile. Since stereotypes are formed locally, recommendations stem from the trustor's own personal experiences and perspective. Historical behavioral information, when available, can be used to refine the analysis. According to our experiments using Epinions.com dataset, StereoTrust compares favorably with existing trust models that use different kinds of information and more complete historical information.

show abstract

Section: Related Workmentioning

confidence: 99%

Trust beyond reputation: A computational trust model based on stereotypes

Liu

Datta

Rządca

2013

Electronic Commerce Research and Applications

View full text Add to dashboard Cite

show abstract

“…In other words, such systems collect feedback, subjective observations which form the basis for trust value computation [38,40].…”

Section: Degree Of Autonomymentioning

confidence: 99%

Trust in collaborative web applications

West

Chang

Venkatasubramanian

et al. 2012

Future Generation Computer Systems

View full text Add to dashboard Cite

Collaborative functionality is increasingly prevalent in web applications. Such functionality permits individuals to add -and sometimes modify -web content, often with minimal barriers to entry. Ideally, large bodies of knowledge can be amassed and shared in this manner. However, such software also provide a medium for nefarious persons to operate. By determining the extent to which participating content/agents can be trusted, one can identify useful contributions. In this work, we define the notion of trust for Collaborative Web Applications and survey the state-of-the-art for calculating, interpreting, and presenting trust values. Though techniques can be applied broadly, Wikipedia's archetypal nature makes it a focal point for discussion. KeywordsCollaborative web applications, trust, reputation, Wikipedia AbstractCollaborative functionality is increasingly prevalent in web applications. Such functionality permits individuals to add -and sometimes modify -web content, often with minimal barriers to entry. Ideally, large bodies of knowledge can be amassed and shared in this manner. However, such software also provide a medium for nefarious persons to operate. By determining the extent to which participating content/agents can be trusted, one can identify useful contributions. In this work, we define the notion of trust for Collaborative Web Applications and survey the state-of-the-art for calculating, interpreting, and presenting trust values. Though techniques can be applied broadly, Wikipedia's archetypal nature makes it a focal point for discussion.

show abstract

“…For example, we might take a value of 0 to indicate that there is no trust between the agents in question and a value of 1 to indicate the fullest possible degree of trust between the agents. Other instantiations of O might contain more structure, such as the tuple of numbers used in subjective logic [45,64,90].…”

Section: Trust Networkmentioning

confidence: 99%

Using argumentation to reason about trust and belief

Tang

Cai

McBurney

et al. 2011

Journal of Logic and Computation

View full text Add to dashboard Cite

Trust is a mechanism for managing the uncertainty about autonomous entities and the information they store, and so can play an important role in any decentralized system. As a result, trust has been widely studied in multiagent systems and related fields such as the semantic web. Here we introduce a formal system of argumentation that can be used to reason using information about trust. This system is described as a set of graphs, which makes it possible to combine our approach with conventional representations of trust between individuals where the relationships between individuals are given in the form of a graph. The resulting system can easily relate the grounds of an argument to the agent that supplied the information, and can be used as the basis to compute Dungian notions of acceptability that take trust into account. We explore some of the properties of these argumentation graphs, examine the computation of trust and belief in the graphs, and illustrate the capabilities of the system on an example from the trust literature.

show abstract

Optimal Trust Network Analysis with Subjective Logic

Abstract: Trust network analysis with subjective logic (TNA-SL)

Cited by 237 publications

References 5 publications

Trust beyond reputation: A computational trust model based on stereotypes

Trust beyond reputation: A computational trust model based on stereotypes

Trust in collaborative web applications

Using argumentation to reason about trust and belief

Contact Info

Product

Resources

About