A Rule-Based Trust Negotiation System

Bonatti, Piero A.; Coi, Juri Luca De; Olmedilla, Daniel; Sauro, Luigi

doi:10.1109/tkde.2010.83

Cited by 30 publications

(25 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Experimental result such as those reported by Bonatti et al (2010) show that there are no immediate issues related to performance when using these policies. Indeed, currently, real-world policies are not very large, partly because trust negotiation systems are not yet widely deployed; therefore, the application of articulated policies would place an excessive burden on users.…”

Section: Scalabilitymentioning

confidence: 78%

See 1 more Smart Citation

On the integration of trust with negotiation, argumentation and semantics

Bonatti

Oliveira

Sabater-Mir

et al. 2013

The Knowledge Engineering Review

Self Cite

View full text Add to dashboard Cite

Agreement Technologies are needed for autonomous agents to come to mutually acceptable agreements, typically on behalf of humans. These technologies include trust computing, negotiation, argumentation and semantic alignment. In this paper, we identify a number of open questions regarding the integration of computational models and tools for trust computing with negotiation, argumentation and semantic alignment. We consider these questions in general and in the context of applications in open, distributed settings such as the grid and cloud computing.

show abstract

Section: Scalabilitymentioning

confidence: 78%

“…Remarkably, in some trust negotiation systems like Protune (see Bonatti & Olmedilla, 2005;Bonatti et al, 2010) agents exchange their requirements by disclosing selected parts of their policies in the form of logic programming rules. transactions) in direct as well as indirect ways (like reputation systems do, for example).…”

Section: Semantics For Trustmentioning

confidence: 99%

On the integration of trust with negotiation, argumentation and semantics

Bonatti

Oliveira

Sabater-Mir

et al. 2013

The Knowledge Engineering Review

Self Cite

View full text Add to dashboard Cite

show abstract

“…Using ConSpec for our work is motivated by 3 reasons: (1) ConSpec was designed for specifying security properties; (2) it also supports the monitoring of security properties at runtime (eg, see Asim et al); and (3) by using a language that is independent from the underlying service technologies, we can support different service technologies (eg, RESTful services, WSDL‐compliant services) at the same time. Our work can easily be adapted to other service specification languages that support security properties such as Unified Services Description Language, PROTUNE, or combinations of XACML and WSDL…”

Section: Modelling Secure Servicesmentioning

confidence: 99%

Modelling, validating, and ranking of secure service compositions

et al. 2017

View full text Add to dashboard Cite

Summary In the world of large‐scale applications, software as a service (SaaS) in general and use of microservices, in particular, is bringing service‐oriented architectures to a new level: Systems in general and systems that interact with human users (eg, sociotechnical systems) in particular are built by composing microservices that are developed independently and operated by different parties. At the same time, SaaS applications are used more and more widely by enterprises as well as public services for providing critical services, including those processing security or privacy of relevant data. Therefore, providing secure and reliable service compositions is increasingly needed to ensure the success of SaaS solutions. Building such service compositions securely is still an unsolved problem. In this paper, we present a framework for modelling, validating, and ranking secure service compositions that integrate both automated services as well as services that interact with humans. As a unique feature, our approach for ranking services integrates validated properties (eg, based on the result of formally analysing the source code of a service implementation) as well as contractual properties that are part of the service level agreement and, thus, not necessarily ensured on a technical level.

show abstract

“…Another semantic policy language is Protune [22]. It is based on logic programming rules, including negation.…”

Section: Related Workmentioning

confidence: 99%

A Self-Policing Policy Language

Speiser

Studer

2010

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. Formal policies allow the non-ambiguous definition of situations in which usage of certain entities are allowed, and enable the automatic evaluation whether a situation is compliant. This is useful for example in applications using data provided via standardized interfaces. The low technical barriers of integrating such data sources is in contrast to the manual evaluation of natural language policies as they currently exist. Usage situations can themselves be regulated by policies, which can be restricted by the policy of a used entity. Consider for example the Google Maps API, which requires that applications using the API must be available without a fee, i.e. the application's policy must not require a payment. In this paper we present a policy language that can express such constraints on other policies, i.e. a self-policing policy language. We validate our approach by realizing a use case scenario, using a policy engine developed for our language.

show abstract

A Rule-Based Trust Negotiation System

Cited by 30 publications

References 28 publications

On the integration of trust with negotiation, argumentation and semantics

On the integration of trust with negotiation, argumentation and semantics

Modelling, validating, and ranking of secure service compositions

A Self-Policing Policy Language

Contact Info

Product

Resources

About