Privacy Leakage of Search-based Multi-agent Planning Algorithms

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Privacy Leakage of Search-based Multi-agent Planning Algorithms

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Privacy Leakage of Search-based Multi-agent Planning Algorithms

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

<a href="/cs/project/GJ18-24965Y" target="_blank" >GJ18-24965Y: Multi-agentní plánování s ochranou soukromých informací</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Autonomous Agents and Multi-Agent Systems

ISSN

1387-2532

e-ISSN

1573-7454

Svazek periodika

36

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

32

Strana od-do

1-32

Kód UT WoS článku

000820223500001

EID výsledku v databázi Scopus

2-s2.0-85133331223