12,000

We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK

93%

93% of Lancaster students go into work or further study within six months of graduating

Home > Research > Publications & Outputs > Enhancing privacy in Multi-agent Systems
View graph of relations

« Back

Enhancing privacy in Multi-agent Systems

Research output: Contribution to journalJournal article

Published

Journal publication date2012
JournalAI Communications
Journal number4
Volume25
Number of pages3
Pages377-379
Original languageEnglish

Abstract

In this thesis, we focus on avoiding undesired information collection and information processing in Multi-agent Systems. In order to avoid undesired information collection we propose a decision-making model for agents to decide whether disclosing personal information to other agents is acceptable or not. We also contribute a secure Agent Platform that allows agents to communicate with each other in a confidential fashion. In order to avoid undesired information processing, we propose an identity management model for agents in a Multi-agent System. This model avoids undesired information processing by allowing agents to hold as many identities as needed for minimizing data identifiability.