Abstract
Our human body is well protected by antibodies from our biological immune system. This protection system matured over millions of years and has proven its functionality. In our research we are going to transfer some techniques of a biological immune system to a computer based environment. Our goal is to design a self-protecting middleware which is not vulnerable to malicious events. First off this paper proposes an artificial immune system and evaluates optimal parameter settings. This shows the correlation between the size of a system and the length of the receptors used within antibodies for an efficient detection. Our tests showed that the recognition rate of unknown malicious objects can reach up to 99%. Further on we describe the integration of the immune system into our organic middleware OCĪ¼ and afterwards we propose techniques to minimize the memory space needed for storing the antibodies and to speedup the time needed for detecting malicious messages. We obtained a space minimization by 30% and gained a speedup of 30 with execution time optimization.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Le Boudec, J.-Y., SarafijanoviÄ, S.: An artificial immune system approach to misbehavior detection in mobile ad hoc networks. In: Ijspeert, A.J., Murata, M., Wakamiya, N. (eds.) BioADIT 2004. LNCS, vol.Ā 3141, pp. 396ā411. Springer, Heidelberg (2004)
Burgess, M.: Computer Immunology. In: Twelfth Systems Administration Conference (LISA 1998), Boston, Massachusetts (December 1998)
Corless, R.M., Jeffrey, D.J., Knuth, D.E.: A Sequence of Series for the Lambert W Function. In: International Symposium on Symbolic and Algebraic Computation, Maui, Hawaii, USA, pp. 197ā204. ACM, New York (1997)
de Castro, L.N., Timmis, J.: Artificial Immune Systems: A Novel Paradigm to Pattern Recognition. In: Corchado, J.M., Alonso, L., Fyfe, C. (eds.) Artificial Neural Networks in Pattern Recognition, SOCO 2002, University of Paisley, UK, pp. 67ā84 (2002)
de Castro, L.N., von Zuben, F.J.: Biologically Inspired Computing. Idea Group Publishing (2005)
Dāhaeseleer, P.: An Immunological Approach to Change Detection: Theoretical Results. In: 9th IEEE Computer Security Foundations Workshop, Dromquinna Manor, County Kerry, Ireland. IEEE, Los Alamitos (1996)
Hall, J.M., Frincke, D.A.: An Architecture for Intrusion Detection Modeled After the Human Immune System. In: Proceedings of the International Conference on Computer, Communication and Control Technologies, vol.Ā 6, pp. 75ā78 (2003)
Hart, E., Timmis, J.: Application Areas of AIS: The Past, The Present and The Future. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) ICARIS 2005. LNCS, vol.Ā 3627, pp. 483ā497. Springer, Heidelberg (2005)
Hofmeyr, S.A., Forrest, S.: Architecture for an Artificial Immune System. Evolutionary ComputationĀ 8(4), 45ā68 (2000)
Hofmeyr, S.A.: An Immunological Model of Distributed Detection and Its Application to Computer Security. Ph.D thesis, University of New Mexico (May 1999)
Ji, Z., Dasgupta, D.: Estimating the Detector Coverage in a Negative Selection Algorithm. In: Genetic and Evolutionary Computation Conference (GECCO 2005), Washington DC, pp. 281ā288. ACM, New York (2005)
Kephart, J.O., Chess, D.M.: The Vision of Autonomic Computing, pp. 41ā50. IEEE Computer Society, Los Alamitos (2003)
MĆ¼ller-Schloer, C.: Organic Computing Initiative (April 2004), Published as PDF on: http://www.informatik.uni-augsburg.de/lehrstuehle/sik/research/organiccomputing/download/OC-english.pdf
Rivest, R.: The MD5 Message-Digest Algorithm. Technical Report Request for Comments: 1321, Internet Engineering Task Force (IETF) (April 1992)
Somayaji, A., Hofmeyr, S., Forrest, S.: Principles of a Computer Immune System. In: New Security Paradigms Workshop, Cumbria, UK, pp. 75ā82. ACM, New York (1997)
Trumler, W., Bagci, F., Petzold, J., Ungerer, T.: AMUN - autonomic middleware for ubiquitous environments applied to the smart doorplate. Advanced Engineering InformaticsĀ (19), 243ā252 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
Ā© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pietzowski, A., Satzger, B., Trumler, W., Ungerer, T. (2006). A Bio-inspired Approach for Self-protecting an Organic Middleware with Artificial Antibodies. In: de Meer, H., Sterbenz, J.P.G. (eds) Self-Organizing Systems. EuroNGI IWSOS 2006 2006. Lecture Notes in Computer Science, vol 4124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11822035_17
Download citation
DOI: https://doi.org/10.1007/11822035_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37658-3
Online ISBN: 978-3-540-37669-9
eBook Packages: Computer ScienceComputer Science (R0)