An FPGA hardware architecture of Nilsimsa fingerprinting algorithm

Alireza Monemi*, Muhidin Abdullahi Mohamed, Muhammad Nadzir Marsono

*Corresponding author for this work

    Research output: Chapter in Book/Published conference outputConference publication

    Abstract

    Nilsimsa algorithm is a very effective spam fingerprinting technique. This spam fingerprinting algorithm is formulated for software implementation. In this paper, we present an FPGA hardware architecture of the modified form of Nilsimsa algorithm which has similar accurate with the original software-targeted algorithm. The modification results in hardware resources reduction and execution time speed up. The implemented algorithm works at 123 MHz frequency and has a throughput of 1 byte per 2 clock cycles (494 Megabits per second). Our system also needs an extra 512 clock cycles after receiving the entire of the message to compute the Nilsimsa fingerprint. This means the minimum time for computing the fingerprint of a message with the size of 10 Kbytes is 167 μ s, which is equal to 5988 emails per second. For 100 MHz clock, our proposed architecture is 1400 times faster compared to implementation on 32-bit general-purpose embedded processor, and 24 times faster than the implementation on a modern CPU running on 2.64 GHz clock.

    Original languageEnglish
    Title of host publicationInECCE 2011 - International Conference on Electrical, Control and Computer Engineering
    PublisherIEEE
    Pages124-129
    Number of pages6
    ISBN (Print)9781612842288
    DOIs
    Publication statusPublished - 18 Aug 2011
    Event1st International Conference on Electrical, Control and Computer Engineering 2011, InECCE 2011 - Kuantan, Malaysia
    Duration: 21 Jun 201122 Jun 2011

    Conference

    Conference1st International Conference on Electrical, Control and Computer Engineering 2011, InECCE 2011
    Country/TerritoryMalaysia
    CityKuantan
    Period21/06/1122/06/11

    Keywords

    • Fingerprinting
    • hardware implementation
    • Nilsimsa
    • spam detection

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