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String Kernel Based SVM for Internet Security Implementation

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F09%3APU86245" target="_blank" >RIV/00216305:26230/09:PU86245 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    String Kernel Based SVM for Internet Security Implementation

  • Original language description

    For network intrusion and virus detection, ordinary methods detect malicious network traffic and viruses by examining packets, flow logs or content of memory for any signatures of the attack. This implies that if no signature is known/created in advance,attack detection will be problematical. Addressing unknown attacks detection, we develop in this paper a network traffic and spam analyzer using a string kernel based SVM (support vector machine) supervised machine learning. The proposed method is capable of detecting network attack without known/earlier determined attack signatures, as SVM automatically learning attack signatures from traffic data. For application to internet security, we have implemented the proposed method for spam email detection over the <i>SpamAssasin</i> and <i>E. M. Canada</i> datasets, and network application authentication via real connection data analysis. The obtained above 99% accuracies have demonstrated the usefulness of string kernel SVMs on network sec

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JC - Computer hardware and software

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2009

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Neural Information Processing

  • ISBN

    978-3-642-10682-8

  • ISSN

  • e-ISSN

  • Number of pages

    10

  • Pages from-to

  • Publisher name

    Springer Verlag

  • Place of publication

    Berlin / Heidelberg

  • Event location

    Bangkok

  • Event date

    Dec 1, 2009

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article