Abstract
We have proposed a metaphor “DAnger Susceptible daTa codON” (DASTON) in data subject to processing by Danger Theory (DT) based Artificial Immune System (DAIS). The DASTONs are data chunks or data point sets that actively take part to produce “danger”; here we abstract “danger” as required outcome. To have closer look to the metaphor, this paper furthers biological abstractions for DASTON. Susceptibility of DASTON is important parameter for generating dangerous outcome. In biology, susceptibility of a host to pathogenic activities (potentially dangerous activities) is related to polymorphism. Interestingly, results of experiments conducted for system call DASTONs are in close accordance to biological theory of polymorphism and susceptibility. This shows that computational data (system calls in this case) exhibit biological properties when processed with DT point of view.
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.
Similar content being viewed by others
References
Iqbal, A., Maarof, M.A.: Towards Danger Theory based Artificial APC Model: Novel Metaphor for Danger Susceptible Data Codons. In: Nicosia, G., Cutello, V., Bentley, P.J., Timmis, J. (eds.) ICARIS 2004. LNCS, vol. 3239, pp. 161–174. Springer, Heidelberg (2004)
Aickelin, U., Cayzer, S.: The Danger Theory and Its Application to Artificial Immune Systems. In: Proceedings of the International Conference on Artificial Immune Systems (ICARIS 2002), Edinburgh, UK (2002)
Aicklein, U., Bentley, P., Cayser, S., Kim, J., McLeod, J.: Danger Theory: The Link between AIS and IDS. In: Timmis, J., Bentley, P.J., Hart, E. (eds.) ICARIS 2003. LNCS, vol. 2787, pp. 147–155. Springer, Heidelberg (2003)
Hart, E., Ross, P.: Improving SOSDM: Inspirations from the Danger Theory. In: Timmis, J., Bentley, P.J., Hart, E. (eds.) ICARIS 2003. LNCS, vol. 2787, pp. 194–203. Springer, Heidelberg (2003)
Secker, A., Freitas, A.A., Timmis, J.: A Danger Theory Inspired Approach to Web Mining. In: Timmis, J., Bentley, P.J., Hart, E. (eds.) ICARIS 2003. LNCS, vol. 2787, pp. 156–167. Springer, Heidelberg (2003)
Matzinger, P.: The Danger Model: A Renewed Sense of Self. Science 296, 301–305 (2002)
Matzinger, P.: The Danger Model In Its Historical Context. Scand. J. Immunol. 54, 4–9 (2001)
Gallucci, S., Lolkema, M., Matzinger, P.: Natural Adjuvants: Endogenous Activators of Dendritic Cells. Nature Medicine 5(11), 1249–1255 (1999)
Matzinger, P.: The Real Function of The Immune System, http://cmmg.biosci.wayne.edu/asg/polly.html (last accessed on 06-04-04)
Matzinger, P.: An Innate sense of danger. Seminars in Immunology 10, 399–415 (1998)
Lutz, M.A., Gervais, F., Bernstein, A., Hattel, A.L., Correll, P.H.: STK Receptor Tyrosine Kinase Regulates Susceptibility to Infection with Listeria Monocytogenes. Infection and Immunity 70(1), 416–418 (2002)
Roy, S., Hill, A.V.S., Knox, K., Griffithsand, D., Crook, D.: Association of Common Genetic Variant with Susceptibility to Invasive Pneumococcal Disease. BMJ 324, 1369 (2002)
Goldmann, W.: The Significance of Genetic Control in TSEs. MicrobiologyToday 30, 170–171 (2003)
Blackwell, J.: Genetics and Genomics in Infectious Disease, CIMR Research Report (2002), http://www.cimr.cam.ac.uk/resreports/report2002/pdf/blackwell_low.pdf (last accessed on 06-04-04)
Coussens, P.M., Tooker, B., Nobis, W., Coussens, M.J.: Genetics and Genomics of Susceptibility to Mycobacterial Infections in Cattle. Online publication on the 2001 IAAFSC web site (2001)
Hill, A.V.S.: Genetics and Genomics of Infectious Disease Susceptibility. British Medical Bulletin. 55(2), 401–413 (1999)
Tavtigian, S.V., et al.: A Candidate Prostate Cancer Susceptibility Gene at Chromosome 17p. Nature Genetics 27, 172–180 (2001)
Casanova, J.-L.: Mendelian Susceptibility to Mycobacterial Infection in Man. Swiss Med. Weekly 131, 445–454 (2001)
Denny, P., Hopes, E., Gingles, N., Broman, K.W., McPheat, W., Morten, J., Alexander, J., Andrew, P.W., Brown, S.D.M.: A major Locus Conferring Susceptibility to Infection by Streptococcus Pneumoniae in Mice. Mammalian Genome 14, 448–453 (2003)
Forrest, S., Balthrop, J., Glickman, M., Ackley, D.: Computation in the Wild. In: Park, K., Willins, W. (eds.) The Internet as a Large-Complex System. Oxford University Press, Oxford (2002)
Intrusion Detection Data Sets, http://www.cs.unm.edu/immsec/systemcalls.htm (last cited on 01-05-2005)
Zhou, Y.-S., Wang, F.-S., Liu, M.-X., Jin, L., Hong, W.-G.: Relationship between susceptibility of hepatitis B virus and gene polymorphism of tumor necrosis factor-a. World Chin. J. Digestol. 13(2), 207–210 (2005)
Kwiatkowski, D.: Susceptibility to infection. BMJ 321, 1061–1065 (2000)
Knapp, S., Hennig, B.J.W.: Interleukin-10 promoter polymorphisms and the outcome of hepatitis C virus infection. Immunogenetics 55, 362–369 (2003)
Hill, A.V.S.: Genetics and genomics of infectious disease susceptibility. British Medical Bulletin 55(2), 401–413 (1999)
Sabouri, A.H., Saito, M.: Polymorphism in the Interleukin-10 Promoter Affects Both Provirus Load and the Risk of Human T Lymphotropic Virus Type I–Associated Myelopathy/Tropical Spastic Paraparesis. Journal of Infectious Diseases 190, 1279–1285 (2004)
Kang, D.-K., Fuller, D., Honavar, V.: Learning Classifiers for Misuse and Anomaly Detection Using a Bag of System Calls Representation. Technical Report ISU-CS-TR 05-06, Computer Science Department, Iowa State University, Ames, IA, USA, March 3 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Iqbal, A., Maarof, M.A. (2005). Polymorphism and Danger Susceptibility of System Call DASTONs. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds) Artificial Immune Systems. ICARIS 2005. Lecture Notes in Computer Science, vol 3627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11536444_28
Download citation
DOI: https://doi.org/10.1007/11536444_28
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28175-7
Online ISBN: 978-3-540-31875-0
eBook Packages: Computer ScienceComputer Science (R0)