Quantifying Privacy Leakage in Multi-Agent Planning. Štolba, M., Tožička, J., & Komenda, A. In Paper abstract bibtex Multi-agent planning using MA-STRIPS-related models is often motivated by the preservation of private information. Such motivation is not only natural for multi-agent systems, but is one of the main reasons, why multi-agent planning (MAP) problems cannot be solved centrally. Although the motivation is common in the literature, formal treatment of privacy is mostly missing. An exception is a definition of two extreme concepts, weak and strong privacy. In this paper, we first analyze privacy leakage in the terms of secure Multi-Party Computation and Quantitative Information Flow. Then, we follow by analyzing privacy leakage of the most common MAP paradigms. Finally, we propose a new theoretical class of secure MAP algorithms and show how the existing techniques can be modified in order to fall in the proposed class.
@INPROCEEDINGS{dmap2016stolba1,
author = {Michal {\v{S}}tolba and Jan To{\v{z}}i{\v{c}}ka and Anton{\'{\i}}n Komenda},
title = {Quantifying Privacy Leakage in Multi-Agent Planning},
abstract = {Multi-agent planning using MA-STRIPS-related models is often motivated by the preservation of private information. Such motivation is not only natural for multi-agent systems, but is one of the main reasons, why multi-agent planning (MAP) problems cannot be solved centrally. Although the motivation is common in the literature, formal treatment of privacy is mostly missing. An exception is a definition of two extreme concepts, weak and strong privacy. In this paper, we first analyze privacy leakage in the terms of secure Multi-Party Computation and Quantitative Information Flow. Then, we follow by analyzing privacy leakage of the most common MAP paradigms. Finally, we propose a new theoretical class of secure MAP algorithms and show how the existing techniques can be modified in order to fall in the proposed class.},
url = {https://icaps16.icaps-conference.org/proceedings/dmap16.pdf#page=83}
}
Downloads: 0
{"_id":"p2kdhZCtXrqmhZTYL","bibbaseid":"tolba-toika-komenda-quantifyingprivacyleakageinmultiagentplanning","downloads":0,"creationDate":"2016-05-19T15:13:08.671Z","title":"Quantifying Privacy Leakage in Multi-Agent Planning","author_short":["Štolba, M.","Tožička, J.","Komenda, A."],"year":null,"bibtype":"inproceedings","biburl":"icaps16.icaps-conference.org/dmap16.bib","bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["Michal"],"propositions":[],"lastnames":["Štolba"],"suffixes":[]},{"firstnames":["Jan"],"propositions":[],"lastnames":["Tožička"],"suffixes":[]},{"firstnames":["Antonín"],"propositions":[],"lastnames":["Komenda"],"suffixes":[]}],"title":"Quantifying Privacy Leakage in Multi-Agent Planning","abstract":"Multi-agent planning using MA-STRIPS-related models is often motivated by the preservation of private information. Such motivation is not only natural for multi-agent systems, but is one of the main reasons, why multi-agent planning (MAP) problems cannot be solved centrally. Although the motivation is common in the literature, formal treatment of privacy is mostly missing. An exception is a definition of two extreme concepts, weak and strong privacy. In this paper, we first analyze privacy leakage in the terms of secure Multi-Party Computation and Quantitative Information Flow. Then, we follow by analyzing privacy leakage of the most common MAP paradigms. Finally, we propose a new theoretical class of secure MAP algorithms and show how the existing techniques can be modified in order to fall in the proposed class.","url":"https://icaps16.icaps-conference.org/proceedings/dmap16.pdf#page=83","bibtex":"@INPROCEEDINGS{dmap2016stolba1,\nauthor = {Michal {\\v{S}}tolba and Jan To{\\v{z}}i{\\v{c}}ka and Anton{\\'{\\i}}n Komenda},\ntitle = {Quantifying Privacy Leakage in Multi-Agent Planning},\nabstract = {Multi-agent planning using MA-STRIPS-related models is often motivated by the preservation of private information. Such motivation is not only natural for multi-agent systems, but is one of the main reasons, why multi-agent planning (MAP) problems cannot be solved centrally. Although the motivation is common in the literature, formal treatment of privacy is mostly missing. An exception is a definition of two extreme concepts, weak and strong privacy. In this paper, we first analyze privacy leakage in the terms of secure Multi-Party Computation and Quantitative Information Flow. Then, we follow by analyzing privacy leakage of the most common MAP paradigms. Finally, we propose a new theoretical class of secure MAP algorithms and show how the existing techniques can be modified in order to fall in the proposed class.},\nurl = {https://icaps16.icaps-conference.org/proceedings/dmap16.pdf#page=83}\n}\n\n","author_short":["Štolba, M.","Tožička, J.","Komenda, A."],"key":"dmap2016stolba1","id":"dmap2016stolba1","bibbaseid":"tolba-toika-komenda-quantifyingprivacyleakageinmultiagentplanning","role":"author","urls":{"Paper":"https://icaps16.icaps-conference.org/proceedings/dmap16.pdf#page=83"},"metadata":{"authorlinks":{}}},"search_terms":["quantifying","privacy","leakage","multi","agent","planning","štolba","tožička","komenda"],"keywords":[],"authorIDs":[],"dataSources":["YTEH97APBj4BGmm5u","oF6o5YwZvH6DhpPhw"]}