Valuations of Possible States (VPS): A Unifying Quantitative Framework for Evaluating Privacy in Collaboration

For agents deployed in real-world settings, such as businesses, universities and research laboratories, it is critical that agents protect their individual users’ privacy when interacting with others entities. Indeed, privacy is recognized as a key motivating factor in design of several multiagent a...

Full description

Saved in:
Bibliographic Details
Main Authors: MAHESWARAN, Rajiv T., Pearce, Jonathan, VARAKANTHAM, Pradeep, Bowring, Emma, Tambe, Milind
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2005
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/994
https://ink.library.smu.edu.sg/context/sis_research/article/1993/viewcontent/SS05_05_011.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.sis_research-1993
record_format dspace
spelling sg-smu-ink.sis_research-19932021-09-02T05:45:15Z Valuations of Possible States (VPS): A Unifying Quantitative Framework for Evaluating Privacy in Collaboration MAHESWARAN, Rajiv T. Pearce, Jonathan VARAKANTHAM, Pradeep Bowring, Emma Tambe, Milind For agents deployed in real-world settings, such as businesses, universities and research laboratories, it is critical that agents protect their individual users’ privacy when interacting with others entities. Indeed, privacy is recognized as a key motivating factor in design of several multiagent algorithms, such as distributed constraint optimization (DCOP) algorithms. Unfortunately, rigorous and general quantitative metrics for analysis and comparison of such multiagent algorithms with respect to privacy loss are lacking. This paper takes a key step towards developing a general quantitative model from which one can analyze and generate metrics of privacy loss by introducing the VPS (Valuations of Possible States) framework. VPS is shown to capture various existing measures of privacy created for specific domains of distributed constraint satisfactions problems (DCSPs). The utility of VPS is further illustrated via analysis of DCOP algorithms, when such algorithms are used by personal assistant agents to schedule meetings among users. In addition, VPS allows us to quantitatively evaluate the properties of several privacy metrics generated through qualitative notions. We obtain the unexpected result that decentralization does not automatically guarantee superior protection of privacy. 2005-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/994 info:doi/10.1145/1082473.1082629 https://ink.library.smu.edu.sg/context/sis_research/article/1993/viewcontent/SS05_05_011.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Artificial Intelligence and Robotics Information Security
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Artificial Intelligence and Robotics
Information Security
spellingShingle Artificial Intelligence and Robotics
Information Security
MAHESWARAN, Rajiv T.
Pearce, Jonathan
VARAKANTHAM, Pradeep
Bowring, Emma
Tambe, Milind
Valuations of Possible States (VPS): A Unifying Quantitative Framework for Evaluating Privacy in Collaboration
description For agents deployed in real-world settings, such as businesses, universities and research laboratories, it is critical that agents protect their individual users’ privacy when interacting with others entities. Indeed, privacy is recognized as a key motivating factor in design of several multiagent algorithms, such as distributed constraint optimization (DCOP) algorithms. Unfortunately, rigorous and general quantitative metrics for analysis and comparison of such multiagent algorithms with respect to privacy loss are lacking. This paper takes a key step towards developing a general quantitative model from which one can analyze and generate metrics of privacy loss by introducing the VPS (Valuations of Possible States) framework. VPS is shown to capture various existing measures of privacy created for specific domains of distributed constraint satisfactions problems (DCSPs). The utility of VPS is further illustrated via analysis of DCOP algorithms, when such algorithms are used by personal assistant agents to schedule meetings among users. In addition, VPS allows us to quantitatively evaluate the properties of several privacy metrics generated through qualitative notions. We obtain the unexpected result that decentralization does not automatically guarantee superior protection of privacy.
format text
author MAHESWARAN, Rajiv T.
Pearce, Jonathan
VARAKANTHAM, Pradeep
Bowring, Emma
Tambe, Milind
author_facet MAHESWARAN, Rajiv T.
Pearce, Jonathan
VARAKANTHAM, Pradeep
Bowring, Emma
Tambe, Milind
author_sort MAHESWARAN, Rajiv T.
title Valuations of Possible States (VPS): A Unifying Quantitative Framework for Evaluating Privacy in Collaboration
title_short Valuations of Possible States (VPS): A Unifying Quantitative Framework for Evaluating Privacy in Collaboration
title_full Valuations of Possible States (VPS): A Unifying Quantitative Framework for Evaluating Privacy in Collaboration
title_fullStr Valuations of Possible States (VPS): A Unifying Quantitative Framework for Evaluating Privacy in Collaboration
title_full_unstemmed Valuations of Possible States (VPS): A Unifying Quantitative Framework for Evaluating Privacy in Collaboration
title_sort valuations of possible states (vps): a unifying quantitative framework for evaluating privacy in collaboration
publisher Institutional Knowledge at Singapore Management University
publishDate 2005
url https://ink.library.smu.edu.sg/sis_research/994
https://ink.library.smu.edu.sg/context/sis_research/article/1993/viewcontent/SS05_05_011.pdf
_version_ 1770570817084588032