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Enhancing privacy in Multi-agent Systems

Research output: Contribution to journalJournal article


<mark>Journal publication date</mark>2012
<mark>Journal</mark>AI Communications
Number of pages3
<mark>Original language</mark>English


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.