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An automated negotiation agent for permission management

An automated negotiation agent for permission management
An automated negotiation agent for permission management
The digital economy is based on data sharing yet citizens have little control about how their personal data is being used. While data management during web and app-based use is already a challenge, as the Internet of Things (IoT) scales up, the number of devices accessing and requiring personal data will go beyond what a person can manually assess in terms of data access requests. Therefore, new approaches are needed for managing privacy preferences at scale and providing active consent around data sharing that can improve fidelity of operation in alignment with user intent. To address this challenge, we introduce a novel agent-based approach to negotiate the permission to exchange private data between users and services. Our agent negotiates based on learned preferences from actual users. To evaluate our agent-based approach, we developed an experimental tool to run on people's own smartphones, where users were asked to share their private, real data (e.g. photos, contacts, etc) under various conditions. The agent autonomously negotiates potential agreements for the user, which they can refine by manually continuing the negotiation. The agent learns from these interactions and updates the user model in subsequent interactions. We find that the agent is able to effectively capture the preferences and negotiate on the user's behalf but, surprisingly, does not reduce user engagement with the system. Understanding how interaction interplays with agent-based automation is a key component to successful deployment of negotiating agents in real-life settings and within the IoT context in particular.
380-390
ACM
Baarslag, Tim
a7c541d8-8141-467b-a08c-7a81cd69920e
Alper, Alan
56790e08-e63b-4577-86d8-234475a1dd72
Gomer, Richard
170145a5-ed38-4f46-ab46-dd8dc956df03
Alam, Muddasser
9a8f7f5d-2a65-4933-8903-d48445358eb8
Charith, Perera
9665e328-6094-4100-a832-ebae88fe2233
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
schraefel, m.c.
ac304659-1692-47f6-b892-15113b8c929f
Baarslag, Tim
a7c541d8-8141-467b-a08c-7a81cd69920e
Alper, Alan
56790e08-e63b-4577-86d8-234475a1dd72
Gomer, Richard
170145a5-ed38-4f46-ab46-dd8dc956df03
Alam, Muddasser
9a8f7f5d-2a65-4933-8903-d48445358eb8
Charith, Perera
9665e328-6094-4100-a832-ebae88fe2233
Gerding, Enrico
d9e92ee5-1a8c-4467-a689-8363e7743362
schraefel, m.c.
ac304659-1692-47f6-b892-15113b8c929f

Baarslag, Tim, Alper, Alan, Gomer, Richard, Alam, Muddasser, Charith, Perera, Gerding, Enrico and schraefel, m.c. (2017) An automated negotiation agent for permission management. In AAMAS 2017: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems. ACM. 0 pp, pp. 380-390.

Record type: Conference or Workshop Item (Paper)

Abstract

The digital economy is based on data sharing yet citizens have little control about how their personal data is being used. While data management during web and app-based use is already a challenge, as the Internet of Things (IoT) scales up, the number of devices accessing and requiring personal data will go beyond what a person can manually assess in terms of data access requests. Therefore, new approaches are needed for managing privacy preferences at scale and providing active consent around data sharing that can improve fidelity of operation in alignment with user intent. To address this challenge, we introduce a novel agent-based approach to negotiate the permission to exchange private data between users and services. Our agent negotiates based on learned preferences from actual users. To evaluate our agent-based approach, we developed an experimental tool to run on people's own smartphones, where users were asked to share their private, real data (e.g. photos, contacts, etc) under various conditions. The agent autonomously negotiates potential agreements for the user, which they can refine by manually continuing the negotiation. The agent learns from these interactions and updates the user model in subsequent interactions. We find that the agent is able to effectively capture the preferences and negotiate on the user's behalf but, surprisingly, does not reduce user engagement with the system. Understanding how interaction interplays with agent-based automation is a key component to successful deployment of negotiating agents in real-life settings and within the IoT context in particular.

Text An_Automated_Negotiation_Agent_for_Permission_Management - Accepted Manuscript
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More information

Accepted/In Press date: 25 January 2017
Published date: 8 May 2017
Venue - Dates: AAMAS 2017: Sixteenth International Conference on Autonomous Agents and Multiagent Systems, Sao Paulo, Brazil, 2017-05-08 - 2017-05-12
Organisations: Agents, Interactions & Complexity, Electronics & Computer Science

Identifiers

Local EPrints ID: 405608
URI: https://eprints.soton.ac.uk/id/eprint/405608
PURE UUID: 17b7728d-23c7-436f-ac44-f0c79683c299
ORCID for Tim Baarslag: ORCID iD orcid.org/0000-0002-1662-3910

Catalogue record

Date deposited: 07 Feb 2017 12:42
Last modified: 06 Jun 2018 12:22

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