Abstract

This paper introduces a structured goal-oriented agent-based process modelling framework, where advanced security requirements engineering techniques are combined with software security modelling approaches, to provide an environment within which the security managers and the analysts can easily cooperate to discover, verify and validate the new IT system security requirements. Without multi-agent systems engineering methodologies, the realization of complex information systems involving numerous interacting components would be prohibitively expensive, prone to failure and involve timescales unacceptable in today's security environment. By following appropriate methodologies, highly integrated and complex security management & control (SMC) information systems can be built to interact securely on a global scale. This paper presents an approach to design a multi-agent system managing a security management system corporate memory in the form of a distributed semantic Web and describes the resulting architecture. We present an information and knowledge exchange framework to support a distributed security problem solving in a PKI-based network environment domain. It addresses two important issues: (1) how individual agents should be interconnected so that their security capabilities are efficiently used and their security goals are accomplished effectively and efficiently; (2) how the information and knowledge transfer should take place among agents to allow them to respond successfully to user requests and unexpected situations in the security domain. We employ the concepts related to SAMARA - a security architecture multi-agents systems risk assessment. The focus of this paper is dynamic knowledge exchange among SAMARA agents. The co-ordinator agent together with a decision enabling warehouse (DEW) acting as a dynamic knowledge-based security platform plus direct intercommunication among the agents enable facts, commands, and rules to be transferred between SAMARA agents. Knowledge can be exchanged among the agents by using a combination of facts, rules and commands transfers

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