A cooperative immunological approach for detecting network anomaly

Technology and biological systems have now bi-directional relation that each benefits from the other. Biological systems naturally enjoy many attractive features and inherent intelligence that fit in solving many research problems. The natural immune system as one of those biological systems is considered a good source of inspiration to artificial defense systems. It has its own intelligent mechanisms to detect the foreign bodies and fight them and without it, an individual cannot live, even just for several days. The new types of network attacks evolved and became more complex, severe and hard to detect. This resulted in increasing need for network defense systems, and especially those with unordinary approaches or with ability to face the dynamic nature of new and continuously changing network threats. In this work we investigate different AIS theories and show how to combine different ideas to solve problems of network security domain. An Intrusion Detection System (IDS) that apply those ideas was built and tested in a real-time environment to test the pros and cons of Artificial Immune System (AIS) and clarify its applicability. Also some investigation on the vaccination biological process is introduced. A special module was built to perform this process and check its usage and how it could be formulated in artificial life.

[1]  Jonathan Timmis,et al.  Artificial Immune Systems: A New Computational Intelligence Approach , 2003 .

[2]  Thomas Pradeu,et al.  The Self Model and the Conception of Biological Identity in Immunology , 2006 .

[3]  Fabio A. González,et al.  A comparative analysis of artificial immune network models , 2005, GECCO '05.

[4]  Wolfgang Banzhaf,et al.  The use of computational intelligence in intrusion detection systems: A review , 2010, Appl. Soft Comput..

[5]  Leandro Nunes de Castro,et al.  An Overview of Artificial Immune Systems , 2004 .

[6]  Tao Li,et al.  Distributed agents model for intrusion detection based on AIS , 2009, Knowl. Based Syst..

[7]  Alan S. Perelson,et al.  Self-nonself discrimination in a computer , 1994, Proceedings of 1994 IEEE Computer Society Symposium on Research in Security and Privacy.

[8]  Julie Greensmith,et al.  Immune System Approaches to Intrusion Detection - A Review , 2004, ICARIS.

[9]  Stephanie Forrest,et al.  Revisiting LISYS : Parameters and Normal , 2002 .

[10]  Pascal Bouvry,et al.  Anomaly detection in TCP/IP networks using immune systems paradigm , 2007, Comput. Commun..

[11]  Jun He,et al.  A hybrid artificial immune system and Self Organising Map for network intrusion detection , 2008, Inf. Sci..

[12]  Dipankar Dasgupta,et al.  Immunity-Based Intrusion Detection System: A General Framework , 1999 .

[13]  Tim R Mosmann,et al.  Dendritic cells: the immune information management experts , 2004, Nature Immunology.

[14]  Tarek S. Sobh.  Wired and wireless intrusion detection system: Classifications, good characteristics and state-of-the-art , 2006, Comput. Stand. Interfaces.

[15]  Stefan Axelsson,et al.  Intrusion Detection Systems: A Survey and Taxonomy , 2002 .

[16]  D. Dasgupta.  Artificial Immune Systems and Their Applications , 1998, Springer Berlin Heidelberg.

[17]  Morton Swimmer.  Using the danger model of immune systems for distributed defense in modern data networks , 2007, Comput. Networks.

[18]  Marc Ebner,et al.  On The Use Of Negative Selection In An Artificial Immune System , 2002, GECCO.

[19]  Stephanie Forrest,et al.  Principles of a computer immune system , 1998, NSPW '97.

[20]  Mohammad Reza Ahmadi,et al.  An Intrusion Prediction Technique Based on Co-evolutionary Immune System for Network Security (CoCo-IDP) , 2009, Int. J. Netw. Secur..

[21]  Jamie Paul Twycross,et al.  Integrated innate and adaptive artificial immune systems applied to process anomaly detection , 2007 .

[22]  Jonathan Timmis,et al.  Application areas of AIS: The past, the present and the future , 2008, Appl. Soft Comput..

[23]  Jung-Min Park,et al.  Network anomaly detection with incomplete audit data , 2007, Comput. Networks.

[24]  Stephanie Forrest,et al.  Immunity by design: an artificial immune system , 1999 .

[25]  Jeffrey O. Kephart,et al.  A biologically inspired immune system for computers , 1994 .

[26]  Yoshiki Uchikawa,et al.  A gait acquisition of a 6-legged robot using immune networks , 1994, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'94).

[27]  P. Matzinger.  Tolerance, danger, and the extended family. , 1994, Annual review of immunology.

[28]  Jonathan Timmis,et al.  Artificial immune systems - a new computational intelligence paradigm , 2002 .

[29]  Gabriel Maciá-Fernández,et al.  Anomaly-based network intrusion detection: Techniques, systems and challenges , 2009, Comput. Secur..

[30]  Uwe Aickelin,et al.  libtissue - implementing innate immunity , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[31]  Jean-Yves Le Boudec,et al.  An Artificial Immune System Approach to Misbehavior Detection in Mobile Ad Hoc Networks , 2004, BioADIT.

[32]  Fabio A. González,et al.  An immunity-based technique to characterize intrusions in computer networks , 2002, IEEE Trans. Evol. Comput..

[33]  P. Matzinger.  The Danger Model: A Renewed Sense of Self , 2002, Science.