Secure Distributed Constraint Satisfaction: Reaching Agreement without Revealing Private Information

Yokoo, Makoto; Suzuki, Koutarou; Hirayama, Katsutoshi

doi:10.1007/3-540-46135-3_26

Cited by 40 publications

(40 citation statements)

References 9 publications

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“…Recent studies on privacy have shown that DisCSPs can be solved with complete privacy, i.e. no data loss by agents besides the result of the search [14,16,22]. However, this level of privacy requires the use of cryptographic and encryption tools which result in a substantial loss in efficiency.…”

Section: Privacy In Afcmentioning

confidence: 99%

Asynchronous Forward-checking for DisCSPs

Meisels

Zivan

2007

Constraints

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A new search algorithm for solving distributed constraint satisfaction problems (DisCSPs) is presented. Agents assign variables sequentially, but perform forward checking asynchronously. The asynchronous forward-checking algorithm (AFC) is a distributed search algorithm that keeps one consistent partial assignment at all times. Forward checking is performed by sending copies of the partial assignment to all unassigned agents concurrently. The algorithm is described in detail and its correctness proven. The sequential assignment method of AFC leads naturally to dynamic ordering of agents during search. Several ordering heuristics are presented. The three best heuristics are evaluated and shown to improve the performance of AFC with static order by a large factor. An experimental comparison of AFC to asynchronous backtracking ( ABT) on randomly generated DisCSPs is also presented. AFC with ordering heuristics outperforms ABT by a large factor on the harder instances of random DisCSPs. These results hold for two measures of performance: number of non-concurrent constraints checks and number of messages sent.

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Section: Privacy In Afcmentioning

confidence: 99%

Asynchronous Forward-checking for DisCSPs

Meisels

Zivan

2007

Constraints

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“…This is certainly a limitation compared to other practical implementations without privacy, but the priority in our scheme is to ensure verifiability and privacy (see Section VI-A on page 6). The cryptographic DCSP approach in [5] shares the same limitation while being not fully verifiable and substantially more complex.…”

Section: Results Publicationmentioning

confidence: 99%

“…As privacy is merely a secondary aspect in DCOP (and many schemes in fact leak information [3], [4] or are not verifiable [5]; despite high complexity), we frame our contribution in the context of e-voting, where exact security analyzes with regard to voter anonymity have a longer tradition.…”

Section: A Single Event Scheduling Problemmentioning

confidence: 99%

Privacy-Enhanced Event Scheduling

Kellermann

Böhme

2009

2009 International Conference on Computational Science and Engineering

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Abstract-Event schedulers, well-known from groupware and social software, typically share the problem that they disclose detailed availability patterns of their users. This paper distinguishes event scheduling from electronic voting and proposes a privacy-enhanced event scheduling scheme. Based on superposed sending and Diffie-Hellman key agreement, it is designed to be efficient enough for practical implementations while requiring minimal trust in a central entity. Protocols to enable dynamic joining and leaving of participants are given.

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“…This criteria is widely believed to be valuable and adaptable for large, open, and/or dynamic distributed problems. It is also perceived as an alternative approach to privacy requirements (Silaghi & Faltings, 2002;Wallace & Silaghi, 2004;Yokoo, Suzuki, & Hirayama, 2002;Silaghi & Mitra, 2004).…”

Section: Introductionmentioning

confidence: 99%

ADOPT-ing: unifying asynchronous distributed optimization with asynchronous backtracking

Silaghi

Yokoo

2008

Auton Agent Multi-Agent Syst

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This article presents an asynchronous algorithm for solving Distributed Constraint Optimization problems (DCOPs). The proposed technique unifies asynchronous backtracking (ABT) and asynchronous distributed optimization (ADOPT) where valued nogoods enable more flexible reasoning and more opportunities for communication, leading to an important speed-up. While feedback can be sent in ADOPT by COST messages only to one predefined predecessor, our extension allows for sending such information to any relevant agent. The concept of valued nogood is an extension by Dago and Verfaille of the concept of classic nogood that associates the list of conflicting assignments with a cost and, optionally, with a set of references to culprit constraints.DCOPs have been shown to have very elegant distributed solutions, such as ADOPT, distributed asynchronous overlay (DisAO), or DPOP. These algorithms are typically tuned to minimize the longest causal chain of messages as a measure of how the algorithms will scale for systems with remote agents (with large latency in communication). ADOPT has the property of maintaining the initial distribution of the problem. To be efficient, ADOPT needs a preprocessing step consisting of computing a Depth-First Search (DFS) tree on the constraint graph. Valued nogoods allow for automatically detecting and exploiting the best DFS tree compatible with the current ordering. To exploit such DFS trees it is now sufficient to ensure that they exist. Also, the inference rules available for valued nogoods help to exploit schemes of communication where more feedback is sent to higher priority agents. Together they result in an order of magnitude improvement.

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Secure Distributed Constraint Satisfaction: Reaching Agreement without Revealing Private Information

Cited by 40 publications

References 9 publications

Asynchronous Forward-checking for DisCSPs

Asynchronous Forward-checking for DisCSPs

Privacy-Enhanced Event Scheduling

ADOPT-ing: unifying asynchronous distributed optimization with asynchronous backtracking

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