Privacy Leakage of Search-based Multi-agent Planning Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00358677" target="_blank" >RIV/68407700:21230/22:00358677 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/s10458-022-09568-4" target="_blank" >https://doi.org/10.1007/s10458-022-09568-4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10458-022-09568-4" target="_blank" >10.1007/s10458-022-09568-4</a>
Alternative languages
Result language
angličtina
Original language name
Privacy Leakage of Search-based Multi-agent Planning Algorithms
Original language description
Privacy preservation has become one of the crucial research topics in multi-agent planning. A number of techniques to preserve private information throughout the planning process have emerged. One major difficulty of such research is the comparison of properties related to privacy among such techniques. A metric allowing for comparison of such privacy preservation was introduced only recently, having a number of drawbacks such as prohibitive computational complexity. In this work we strengthen the theoretical foundations and simplify the metric in order to be practically usable. Moreover, we test the usability of the metric in an analysis of various techniques in multi-agent heuristic computation and search, determining which are the most beneficial in terms of privacy preservation. We also evaluate the techniques in terms of the classical IPC score to assess their impact on the overall planning performance. The results are somewhat surprising and show that extracting any privacy-related information even from the simplest variant of heuristic search is a very complicated task. Existing techniques such as distributed heuristic and sending only relevant states is shown to reduce the privacy leakage even more.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GJ18-24965Y" target="_blank" >GJ18-24965Y: Privacy Preserving Multi-agent Planning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Autonomous Agents and Multi-Agent Systems
ISSN
1387-2532
e-ISSN
1573-7454
Volume of the periodical
36
Issue of the periodical within the volume
2
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
32
Pages from-to
1-32
UT code for WoS article
000820223500001
EID of the result in the Scopus database
2-s2.0-85133331223