Soft constraint propagation and solving in CHRs

Bistarelli, Stefano; Frühwirth, Thom; Marte, Michael

doi:10.1145/508791.508793

Cited by 17 publications

(8 citation statements)

References 8 publications

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“…As a future work, we plan to extend in SWI-Prolog the existent CHR module implementing soft constraints [3], by adding the ÷ operator inside the soft module. In this way we could implement a stand-alone policy-based authorization system based on constraint programming.…”

Section: Discussionmentioning

confidence: 99%

A Formal Framework for Trust Policy Negotiation in Autonomic Systems: Abduction with Soft Constraints

Bistarelli

Martinelli

Santini

2010

Lecture Notes in Computer Science

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Abstract. We show that soft constraints can be used to model logical reasoning, that is deduction and abduction (and induction). In particular, we focus on the abduction process and we show how it can be implemented with a (soft) constraint removal operator. As a running application example throughout the paper, we reason with access control policies and credentials. In this way, we can associate the level of preference defined by the "softness" of the constraint with a "level" of trust. The main benefit comes during the process of automated access authorization based on trust: soft constraint operations can be easily adopted to measure the level of trust required for each operation. Moreover, when the level is not sufficient, abduction can be used to compute the missing credentials and the levels that grant the access, making the request a (weighted) logical consequence. The proposed framework can be used to automate the deduction-abduction negotiation processes.

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Section: Discussionmentioning

confidence: 99%

A Formal Framework for Trust Policy Negotiation in Autonomic Systems: Abduction with Soft Constraints

Bistarelli

Martinelli

Santini

2010

Lecture Notes in Computer Science

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“…While mechanical analysis was outside our aims, we have implemented a mechanical checker for l-confidentiality on top of the existing Constraint Handling Rule (CHR) framework [3]. For example, when we input the policy SCSP for the Needham-Schroeder protocol and the imputable SCSP corresponding to Lowe's attack, the checker outputs checking(principal(a)) checking(principal(b)) attack(n_a, policy_level(unknown), attack_level(traded_1)) checking(principal(c)) attack(enk(k(a),pair(n_a,n_b)), policy_level(unknown), attack_level(traded_1)) attack(n_b, policy_level(unknown), attack_level(traded1))…”

Section: Discussionmentioning

confidence: 99%

Confidentiality Levels and Deliberate/Indeliberate Protocol Attacks

Bella

Bistarelli

2004

Security Protocols

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Abstract. A formal definition of confidentiality is developed using soft (rather than crisp) constraints. The goal is no longer considered as a mere yes/no property as in the existing literature, but gains an extra parameter, the security level. The higher the security level, the stronger the goal. For example, different messages may enjoy different levels of confidentiality, and the same message may enjoy different levels of confidentiality for different principals. On this basis, the notion of indeliberate confidentiality attack can be captured, whereby a principal learns some message not meant for him because of someone else's tampering. The analysis of Lowe's attack on the Needham-Schroeder protocol reveals a new weakness.

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“…CHR [43,42,15,41] is a committed-choice declarative language which has been originally designed for writing constraint solvers and which is nowadays a general purpose language.…”

Section: Constraint Handling Rules: Notationmentioning

confidence: 99%

Constraints meet concurrency

Mauro

2015

Constraints

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We investigate the benefits that emerge when the fields of constraint programming and concurrency meet. On one hand, constraints can be use in concurrency theory to increase the conciseness and the expressive power of concurrent languages from a pragmatic point of view. On the other hand, problems modeled by using constraints can be solved faster and more efficiently using a concurrent system. We explore both directions providing two separate lines of contribution. Firstly we study the expressive power of a concurrent language, namely Constraint Handling Rules, that supports constraints as a primitive construct. We show what features of this language make it Turing powerful. Then we propose a framework to solve constraint problems that is intended to be deployed on a concurrent system. For the development of this framework we used the concurrent language Jolie following the Service Oriented paradigm. Based on this experience, we also propose an extension to Service Oriented Languages to overcome some of their limitations and to improve the development of concurrent applications. Needless to say, I am also in debt with my coauthors:

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Soft constraint propagation and solving in CHRs

Cited by 17 publications

References 8 publications

A Formal Framework for Trust Policy Negotiation in Autonomic Systems: Abduction with Soft Constraints

A Formal Framework for Trust Policy Negotiation in Autonomic Systems: Abduction with Soft Constraints

Confidentiality Levels and Deliberate/Indeliberate Protocol Attacks

Constraints meet concurrency

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