Hybrid Multi Agent-Neural Network Intrusion Detection with Mobile Visualization

A multiagent system that incorporates an Artificial Neural Networks based Intrusion Detection System (IDS) has been defined to guaranty an efficient computer network security architecture. The proposed system facilitates the intrusion detection in dynamic networks. This paper presents the structure of the Mobile Visualization Connectionist Agent-Based IDS, more flexible and adaptable. The proposed improvement of the system in this paper includes deliberative agents that use the artificial neural network to identify intrusions in computer networks. The agent based system has been probed through anomalous situations related to the Simple Network Management Protocol.

[1]  Jörg P. Müller,et al.  Agent UML: A Formalism for Specifying Multiagent Software Systems , 2001, Int. J. Softw. Eng. Knowl. Eng..

[2]  H. Sebastian Seung,et al.  The Rectified Gaussian Distribution , 1997, NIPS.

[3]  Jianhua Ma,et al.  Internet Multimedia Computing - Guest Editors' Introduction , 2001, Int. J. Softw. Eng. Knowl. Eng..

[4]  John W. Tukey,et al.  A Projection Pursuit Algorithm for Exploratory Data Analysis , 1974, IEEE Transactions on Computers.

[5]  Álvaro Herrero,et al.  Detecting Compounded Anomalous SNMP Situations Using Cooperative Unsupervised Pattern Recognition , 2005, ICANN.

[6]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[7]  LiaoYihua.  Use of K-Nearest Neighbor classifier for intrusion detection11An earlier version of this paper is to appear in the Proceedings of the 11th USENIX Security Symposium, San Francisco, CA, August 2002 , 2002 .

[8]  J. Bajo,et al.  Hybrid multi-agent architecture as a real-time problem-solving model , 2008, Expert Syst. Appl..

[9]  Steve Wilson,et al.  APHIDS: A Mobile Agent-Based Programmable Hybrid Intrusion Detection System , 2004, MATA.

[10]  Álvaro Herrero,et al.  A Comparison of Neural Projection Techniques Applied to Intrusion Detection Systems , 2007, IWANN.

[11]  H. M. Faheem,et al.  A multi-agent based system for intrusion detection , 2003 .

[12]  Arputharaj Kannan,et al.  Intelligent Multi-agent Based Genetic Fuzzy Ensemble Network Intrusion Detection , 2004, ICONIP.

[13]  Eugene H. Spafford,et al.  Intrusion detection using autonomous agents , 2000, Comput. Networks.

[14]  Thomas Magedanz,et al.  Mobility Aware Technologies and Applications, Second International Workshop, MATA 2005, Montreal, Canada, October 17-19, 2005, Proceedings , 2004, MATA.

[15]  Sultan Aljahdali,et al.  Best hybrid classifiers for intrusion detection , 2006, J. Comput. Methods Sci. Eng..

[16]  Álvaro Herrero,et al.  MOVICAB-IDS: Visual Analysis of Network Traffic Data Streams for Intrusion Detection , 2006, IDEAL.

[17]  Fabio A. González,et al.  CIDS: An agent-based intrusion detection system , 2005, Comput. Secur..

[18]  Sergio M. Savaresi,et al.  Unsupervised learning techniques for an intrusion detection system , 2004, SAC '04.

[19]  V. Rao Vemuri,et al.  Use of K-Nearest Neighbor classifier for intrusion detection , 2002, Comput. Secur..

[20]  Emilio Corchado,et al.  Connectionist Techniques For The Identification And Suppression Of Interfering Underlying Factors , 2003, Int. J. Pattern Recognit. Artif. Intell..

[21]  Christin Schäfer,et al.  Learning Intrusion Detection: Supervised or Unsupervised? , 2005, ICIAP.

[22]  Emilio Corchado,et al.  Maximum and Minimum Likelihood Hebbian Learning for Exploratory Projection Pursuit , 2002, ICANN.

[23]  Grant Dick,et al.  Feature Selection of Intrusion Detection Data using a Hybrid Genetic Algorithm/KNN Approach , 2003, HIS.

[24]  Nicholas R. Jennings,et al.  The Gaia Methodology for Agent-Oriented Analysis and Design , 2000, Autonomous Agents and Multi-Agent Systems.

[25]  Franco Zambonelli,et al.  Developing multiagent systems: The Gaia methodology , 2003, TSEM.

[26]  Juan M. Corchado,et al.  Development of CBR-BDI Agents , 2005, Int. J. Comput. Sci. Appl..

[27]  R. J. Zheng,et al.  Mobile Agents for Network Intrusion Resistance , 2006, APWeb Workshops.

[28]  Álvaro Herrero,et al.  Testing CAB-IDS Through Mutations: On the Identification of Network Scans , 2006, KES.

[29]  S. T. Sarasamma,et al.  Hierarchical Kohonenen net for anomaly detection in network security , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[30]  Juan M. Corchado,et al.  Constructing deliberative agents with case‐based reasoning technology , 2003, Int. J. Intell. Syst..