All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Deep Packet Inspection in FPGAs via Approximate Nondeterministic Automata

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU132977" target="_blank" >RIV/00216305:26230/19:PU132977 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.fit.vut.cz/research/publication/11951/" target="_blank" >https://www.fit.vut.cz/research/publication/11951/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/FCCM.2019.00025" target="_blank" >10.1109/FCCM.2019.00025</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Deep Packet Inspection in FPGAs via Approximate Nondeterministic Automata

  • Original language description

    Deep packet inspection via regular expression (RE) matching is a crucial task of network intrusion detection systems (IDSes), which secure Internet connection against attacks and suspicious network traffic. Monitoring high-speed computer networks (100 Gbps and faster) in a single-box solution demands that the RE matching, traditionally based on finite automata (FAs), is accelerated in hardware. In this paper, we describe a novel FPGA architecture for RE matching that is able to process network traffic beyond 100 Gbps. The key idea is to reduce the required FPGA resources by leveraging approximate nondeterministic FAs (NFAs). The NFAs are compiled into a multi-stage architecture starting with the least precise stage with a high throughput and ending with the most precise stage with a low throughput. To obtain the reduced NFAs, we propose new approximate reduction techniques that take into account the profile of the network traffic. Our experiments showed that using our approach, we were able to perform matching of large sets of REs from Snort, a popular IDS, on unprecedented network speeds.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/LQ1602" target="_blank" >LQ1602: IT4Innovations excellence in science</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2019

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of the 27th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM)

  • ISBN

    978-1-7281-1132-2

  • ISSN

  • e-ISSN

  • Number of pages

    9

  • Pages from-to

    109-117

  • Publisher name

    Institute of Electrical and Electronics Engineers

  • Place of publication

    San Diego, CA

  • Event location

    San Diego, CA

  • Event date

    Apr 28, 2019

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000491873200016