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A Neural-Based Agent for IP Traffic Scanning and Worm Detection

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Artificial Intelligence and Soft Computing - ICAISC 2004 (ICAISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

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Abstract

We present a neural approach to worm detection designed as a part of a multi-agent system intended to manage IP networks. The efficiency of virus recognition is about 95%.

This work was supported by the Polish State Committee for Scientific Research (KBN) under Grant No. 3 T11C 054 26.

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Author information

Authors and Affiliations

  1. Institute of Computer Science, Jagiellonian University, Poland, Nawojki 11, 30-072, Cracow

    Andrzej Bielecki & Paweł Hajto

Authors
  1. Andrzej Bielecki
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  2. Paweł Hajto
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. German Research Center of Artificial Intelligence (DFKI), Germany

    Jörg H. Siekmann

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA

    Lotfi A. Zadeh

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© 2004 Springer-Verlag Berlin Heidelberg

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Bielecki, A., Hajto, P. (2004). A Neural-Based Agent for IP Traffic Scanning and Worm Detection. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_126

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_126

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

  • eBook Packages: Springer Book Archive

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