Literature Database Entry


Falko Dressler, "Self-Organized Network Security Facilities based on Bio-inspired Promoters and Inhibitors," in Advances in Biologically Inspired Information Systems - Models, Methods, and Tools, Studies in Computational Intelligence (SCI), vol. 69, Falko Dressler and Iacopo Carreras (Eds.), Springer, 2007, pp. 81–98.


Self-organization techniques based on promoters and inhibitors has been intensively studied in biological systems. Promoters enable an on-demand amplification of reactions to a particular cause. This allows to react quickly with appropriate countermeasures. On the other hand, inhibitors are capable of regulating this uncontrolled amplification by suppressing the reaction. In this paper, we demonstrate the applicability of these mechanisms in a network security scenario consisting of network monitoring elements, attack detection, and firewall devices. Previous work identified most existing detection approaches as not suitable for high-speed networks. This problem can be alleviated by separating the methodologies for network monitoring and for subsequent data analysis. In this paper, we present an adaptation algorithm that allows to manage the individual configuration parameters in order to optimize the overall system. We show the advantages of self-regulating techniques based on promoters and inhibitors that lead to maximized security and that gracefully degradate in case of overload situations. We created a simulation model to verify the algorithms. The results of the conducted simulations encourage further studies in this field.

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Falko Dressler

BibTeX reference

    author = {Dressler, Falko},
    doi = {10.1007/978-3-540-72693-7_5},
    title = {{Self-Organized Network Security Facilities based on Bio-inspired Promoters and Inhibitors}},
    pages = {81--98},
    booktitle = {Advances in Biologically Inspired Information Systems - Models, Methods, and Tools},
    editor = {Dressler, Falko and Carreras, Iacopo},
    isbn = {978-3-540-72692-0},
    publisher = {Springer},
    series = {Studies in Computational Intelligence (SCI)},
    volume = {69},
    year = {2007},

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