The Deterministic Dendritic Cell Algorithm
The Dendritic Cell Algorithm is an immune-inspired algorithm originally based on the function of natural dendritic cells. The original instantiation of the algorithm is a highly stochastic algorithm. While the performance of the algorithm is good when applied to large real-time datasets, it is difficult to analyse due to the number of random-based elements. In this paper a deterministic version of the algorithm is proposed, implemented and tested using a port scan dataset to provide a controllable system. This version consists of a controllable amount of parameters, which are experimented with in this paper. In addition the effects are examined of the use of time windows and variation on the number of cells, both which are shown to influence the algorithm. Finally a novel metric for the assessment of the algorithms output is introduced and proves to be a more sensitive metric than the metric used with the original Dendritic Cell Algorithm.
KeywordsDanger Signal Anomaly Detection Safe Signal Antigen Type Deterministic Version
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- 1.Aickelin, U., Bentley, P., Cayzer, 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)Google Scholar
- 2.Al-Hammadi, Y., Aickelin, U., Greensmith, J.: DCA for detecting bots. In: Proc. of the Congress on Evolutionary Computation (CEC), page tba (to appear, 2008)Google Scholar
- 3.Greensmith, J.: The Dendritic Cell Algorithm. PhD thesis, School of Computer Science, University Of Nottingham (2007)Google Scholar
- 4.Greensmith, J., Aickelin, U., Cayzer, S.: Introducing Dendritic Cells as a novel immune-inspired algorithm for anomaly detection. In: Jacob, C., Pilat, M.L., Bentley, P.J., Timmis, J.I. (eds.) ICARIS 2005. LNCS, vol. 3627, pp. 153–167. Springer, Heidelberg (2005)Google Scholar
- 5.Greensmith, J., Aickelin, U., Feyereisl, J.: The DCA-SOMe comparison: A comparative study between two biologically-inspired algorithms. Evolutionary Intelligence: Special Issue on Artificial Immune Systems (accepted for publication, 2008)Google Scholar
- 6.Greensmith, J., Aickelin, U., Tedesco, G.: Information fusion for anomaly detection with the DCA. Information Fusion (in print) (2008)Google Scholar
- 8.Greensmith, J., Twycross, J., Aickelin, U.: Dendritic cells for anomaly detection. In: Proc. of the Congress on Evolutionary Computation (CEC), pp. 664–671 (2006)Google Scholar
- 9.Lay, N., Bate, I.: Improving the reliability of real-time embedded systems using innate immune techniques. Evolutionary Intelligence: Special Issue on Artificial Immune Systems (2008)Google Scholar
- 12.Oates, R., Kendall, G., Garibaldi, J.: and. Frequency analysis for dendritic cell population tuning: Decimating the dendritic cell. Evolutionary Intelligence: Special Issue on Artificial Immune Systems (2008)Google Scholar