Trust Assessment Using Provenance in Service Oriented Applications

Rajbhandari, Shrija; Contes, Arnaud; Rana, Omer F.; Deora, Vikas; Wootten, Ian

doi:10.1109/edocw.2006.70

Cited by 18 publications

(17 citation statements)

References 11 publications

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“…In this case, the services can be considered as contexts [5]. A trust-aware provider analyzes service-based interactions from trust perspectives and makes decisions accordingly [6].…”

Section: Introductionmentioning

confidence: 99%

“…Although much research have been devoted to develop systems for trust-based access control and decision making [2,5,[7][8][9][10][11][12][13][14][15][16], secret key sharing [17], or appropriate service provider selection [6], to date, no mechanism has been proposed to automate service collaboration for analyzing the trustworthiness of service requestors at run-time. In this paper, we quantify service collaboration from trust perspectives using our trust model called CAT (Context-Aware Trust) [18], and dynamically decide on service requests at run-time based on our proposed trust-based service collaboration algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Collaboration through computation: incorporating trust model into service-based software systems

Uddin

Zulkernine

Ahamed

2009

SOCA

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The open and dynamic nature of service-based software systems necessitates spontaneous and trustworthy interactions between collaborating entities. Service providers are exposed to users spanned across multiple organizational domains, so can be exploited by potentially untrustworthy service requestors. Given that, service providers need to trust requestors before granting them with services. Trust encompasses a number of quality attributes (e.g., security, competence, honesty) and helps in dynamic decision making. In this paper, we present a trust-based service collaboration approach, facilitated by the analysis of service-based interactions between service providers and requestors, and recommendations between service providers. Service providers exchange recommendations to convey their trust on requestors. This collaboration is quantified using our proposed trust model, called CAT, a Context-Aware Trust model based on service-based interactions by considering services as contexts. We identify a number of collaboration-based trust properties including risk and context-awareness and incorporate them in CAT. A context-similarity parameter is introduced to decide on similar services. A time-based ageing parameter is proposed to decrease trust values over time without any further interactions. Direct and indirect recommendations from other service providers are included in total trust calculation, with a path-based ageing parameter applying over indirect recommendations. A mechanism to calculate the accuracy of recommendations is proposed to differentiate between reliable and unreliable recommendations. These calculation schemes are employed in a trust-based service collaboration algorithm to automatically decide on granting services to requestors. The approach is elaborated using examples from file sharing applications, and successfully evaluated by implementing a prototype service-based file sharing grid.

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“…In this case, the services can be considered as contexts [5]. A trust-aware provider analyzes service-based interactions from trust perspectives and makes decisions accordingly [6].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Collaboration through computation: incorporating trust model into service-based software systems

Uddin

Zulkernine

Ahamed

2009

SOCA

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“…One of the earliest approaches traversed a decision tree with respect to provenance records to measure reputation [12]. Within the domain of information provision, a richer assessment can be obtained by considering the provenance path of information, the trustworthiness of the information itself, and the reliability of the provider to assess reputation [5,21].…”

Section: Introductionmentioning

confidence: 99%

Incorporating Mitigating Circumstances into Reputation Assessment

Miles

Griffiths

2015

Communications in Computer and Information Science

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Abstract. Reputation enables customers to select between providers, and balance risk against other aspects of service provision. For new providers that have yet to establish a track record, negative ratings can significantly impact on their chances of being selected. Existing work has shown that malicious or inaccurate reviews, and subjective differences, can be accounted for. However, an honest balanced review of service provision may still be an unreliable predictor of future performance if the circumstances differ. Specifically, mitigating circumstances may have affected previous provision. For example, while a delivery service may generally be reliable, a particular delivery may be delayed by unexpected flooding. A common way to ameliorate such effects is by weighting the influence of past events on reputation by their recency. In this paper, we argue that it is more effective to query detailed records of service provision, using patterns that describe the circumstances to determine the significance of previous interactions.

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“…Rajbhandari et al [323,324,328] use provenance information to evaluate whether an abstract workflow description has been adhered to, and to enable a user executing a workflow-based application to establish trust in the outcome of a physical workflow. Their notion of trust is compositionally derived from the trust in processes (i.e.…”

Section: Data Quality and Trustmentioning

confidence: 99%

The Foundations for Provenance on the Web

Moreau

2010

FNT in Web Science

172

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Provenance, i.e., the origin or source of something, is becoming an important concern, since it offers the means to verify data products, to infer their quality, to analyse the processes that led to them, and to decide whether they can be trusted. For instance, provenance enables the reproducibility of scientific results; provenance is necessary to track attribution and credit in curated databases; and, it is essential for reasoners to make trust judgements about the information they use over the Semantic Web.As the Web allows information sharing, discovery, aggregation, filtering and flow in an unprecedented manner, it also becomes very difficult to identify, reliably, the original source that produced an information item on the Web. Since the emerging use of provenance in niche applications is undoubtedly demonstrating the benefits of provenance, we contend that provenance can and should reliably be tracked and exploited on the Web, and we survey the necessary foundations to achieve such a vision.Using multiple data sources, we have compiled the largest bibliographical database on provenance so far. This large corpus allows us to analyse emerging trends in the research community. Specifically, using the CiteSpace tool, we identify clusters of papers that constitute research fronts, from which we derive characteristics that we use to structure our foundational framework for provenance on the Web. We note that such an endeavour requires a multi-disciplinary approach, since it requires contributions from many computer science sub-disciplines, but also other non-technical fields given the human challenge that is anticipated.To develop our vision, it is necessary to provide a definition of provenance that applies to the Web context. Our conceptual definition of provenance is expressed in terms of processes, and is shown to generalise various definitions of provenance commonly encountered. Furthermore, by bringing realistic distributed systems assumptions, we refine our definition as a query over assertions made by processes.Given that the majority of work on provenance has been undertaken by the database, workflow and e-science communities, we review some of their work, contrasting approaches, and focusing on important topics we believe to be crucial for bringing provenance to the Web, such as abstraction, collections, storage, queries, workflow evolution, semantics and activities involving human interactions.However, provenance approaches developed in the context of databases and workflows essentially deal with closed systems. By that, we mean that workflow or database management systems are in full control of the data they manage, and track their provenance within their own scope, but not beyond. In the context of the Web, a broader approach is required by which chunks of provenance representation can be brought together to describe the provenance of information flowing across multiple systems. This is the specific purpose of the Open Provenance Vision, which is an approach that consists of controlled voc...

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Trust Assessment Using Provenance in Service Oriented Applications

Cited by 18 publications

References 11 publications

Collaboration through computation: incorporating trust model into service-based software systems

Collaboration through computation: incorporating trust model into service-based software systems

Incorporating Mitigating Circumstances into Reputation Assessment

The Foundations for Provenance on the Web

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