Bayesian network-based extension for PGP - Estimating petition support

Marius Silaghi, Song Qui, Toshihiro Matsui, Makoto Yokoo, Katsutoshi Hirayama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Consider the problem of estimating the expected number of distinct eligible voters among the authors of a set of electronic signatures gathered for a petition (or citizen initiative) that has to pass legally required thresholds. We formalize this problem and propose an extension to the Pretty Good Privacy Web Of Trust, a mechanism for reciprocally certifying identities between peers. The extension (a) enables agents to certify additional relevant statements about others, and (b) gives agents opportunities for negative authentication statements (e.g., on ineligibility of an identity). A Bayesian Network model enables inferences on the data provided by the proposed PGP extension. Simulations and an agent-based platform are used to validate the concepts.

Original languageEnglish
Title of host publicationProceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016
EditorsZdravko Markov, Ingrid Russell
PublisherAAAI Press
Pages98-103
Number of pages6
ISBN (Electronic)9781577357568
Publication statusPublished - Jan 1 2016
Event29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016 - Key Largo, United States
Duration: May 16 2016May 18 2016

Publication series

NameProceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016

Other

Other29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016
CountryUnited States
CityKey Largo
Period5/16/165/18/16

Fingerprint

Bayesian networks
Authentication

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence
  • Computer Networks and Communications

Cite this

Silaghi, M., Qui, S., Matsui, T., Yokoo, M., & Hirayama, K. (2016). Bayesian network-based extension for PGP - Estimating petition support. In Z. Markov, & I. Russell (Eds.), Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016 (pp. 98-103). (Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016). AAAI Press.

Bayesian network-based extension for PGP - Estimating petition support. / Silaghi, Marius; Qui, Song; Matsui, Toshihiro; Yokoo, Makoto; Hirayama, Katsutoshi.

Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016. ed. / Zdravko Markov; Ingrid Russell. AAAI Press, 2016. p. 98-103 (Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Silaghi, M, Qui, S, Matsui, T, Yokoo, M & Hirayama, K 2016, Bayesian network-based extension for PGP - Estimating petition support. in Z Markov & I Russell (eds), Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016. Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016, AAAI Press, pp. 98-103, 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016, Key Largo, United States, 5/16/16.
Silaghi M, Qui S, Matsui T, Yokoo M, Hirayama K. Bayesian network-based extension for PGP - Estimating petition support. In Markov Z, Russell I, editors, Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016. AAAI Press. 2016. p. 98-103. (Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016).
Silaghi, Marius ; Qui, Song ; Matsui, Toshihiro ; Yokoo, Makoto ; Hirayama, Katsutoshi. / Bayesian network-based extension for PGP - Estimating petition support. Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016. editor / Zdravko Markov ; Ingrid Russell. AAAI Press, 2016. pp. 98-103 (Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016).
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