Improving the security level of the FUSION@ multi-agent architecture

Authors:
Cristian I. Pinzón;Juan F. De Paz;Dante I. Tapia;Javier Bajo;Juan M. Corchado
Affiliations:
Universidad Tecnológica de Panamá, Campus Metropolitano Dr. Víctor Levi Sasso, Vía Ricardo J. Alfaro, P.O. Box 0819-07289 Panamá, Panama;Departamento de Informática y Automática, Universidad de Salamanca, Plaza de la Merced, s/n, 37008 Salamanca, Spain;Departamento de Informática y Automática, Universidad de Salamanca, Plaza de la Merced, s/n, 37008 Salamanca, Spain;Facultad de Informática, Universidad Pontificia de Salamanca, Compañía 5, 37002 Salamanca, Spain;Departamento de Informática y Automática, Universidad de Salamanca, Plaza de la Merced, s/n, 37008 Salamanca, Spain
Venue:
Expert Systems with Applications: An International Journal
Year:
2012

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Abstract

The use of architectures based on services and multi-agent systems has become an increasingly important part of the solution set used for the development of distributed systems. Nevertheless, these models pose a variety of problems with regards to security. This article presents the Adaptive Intrusion Detection Multi-agent System (AIDeMaS), a mechanism that has been designed to detect and block malicious SOAP messages within distributed systems built by service based architectures. AIDeMaS has been implemented as part of FUSION@, a multi-agent architecture that facilitates the integration of distributed services and applications to optimize the construction of highly-dynamic multi-agent systems. One of the main features of AIDeMaS is that is employs case-based reasoning mechanisms, which provide it with great learning and adaptation capabilities that can be used for classifying SOAP messages. This research presents a case study that uses the ALZ-MAS system, a multi-agent system built around FUSION@, in order to confirm the effectiveness of AIDeMaS. The preliminary results are presented in this paper.