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Enhancing privacy in Multi-agent Systems

Research output: Contribution to journalJournal article


Journal publication date2012
JournalAI Communications
Journal number4
Number of pages3
Original languageEnglish


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.