Arnon Shimoni

Arnon Shimoni

København, Region Hovedstaden, Danmark
2 t følgere 500+ forbindelser

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Om

I design pricing and personalized monetization strategies, as well as build and create…

Tjenester

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Artikler af Arnon

  • SQream DB v2020.2 is out!
    2. aug. 2020

    SQream DB v2020.2 is out!

    Our second release of the year is out. For this release, the primary focus was additional analytical SQL options, as…

    1 Kommentar

Bidrag

Aktivitet

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Erfaring

  • Subaio Grafik

    Subaio

    Copenhagen Metropolitan Area

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    Copenhagen, Capital Region, Denmark

  • -

    Copenhagen, Capital Region, Denmark

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  • -

    Copenhagen, Capital Region, Denmark

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    Remote

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    Greater New York City Area

  • -

    Israel

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Uddannelse

  • Ben-Gurion University of the Negev Grafik

    Ben-Gurion University of the Negev

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    Aktiviteter og foreninger:department student body,class website editor

    Maintained the class website and represented the students in the student body.

  • –

    Aktiviteter og foreninger:School website, Student body

    Built the school website using PHP and MySQL from scratch. Integrated with the school's class management tool.

Licenser og certificeringer

Udgivelser

  • Malicious traffic detection using traffic fingerprinting

    Recipient of the 'Best Student Project' award for 2015, by the Communication Systems Engineering department at Ben Gurion University.

    We consider the problem of detecting malicious traffic in high bandwidth links. With the ever increasing bandwidth and traffic, deep packet inspection interferes with throughput and becomes computationally demanding. We developed a learning algorithm based on the well-known universal compression algorithm Lempel-Ziv 78. We built a proof-of-concept…

    Recipient of the 'Best Student Project' award for 2015, by the Communication Systems Engineering department at Ben Gurion University.

    We consider the problem of detecting malicious traffic in high bandwidth links. With the ever increasing bandwidth and traffic, deep packet inspection interferes with throughput and becomes computationally demanding. We developed a learning algorithm based on the well-known universal compression algorithm Lempel-Ziv 78. We built a proof-of-concept application that emulates a real-world situation and attempts to identify malware. Our algorithm builds a traffic fingerprint for well-known malware using only the time difference between packets. The algorithm then compares the fingerprint against unknown traffic.
    We study the effectiveness of our method with real-world malicious traffic.

    Andre forfattere
    Se udgivelse

Projekter

  • Barkr - Android mass-communication application (native) with Erlang backend server

    Designed and built Erlang server side, built the Android application around a professional design

    Andre skabere

  • VANET simulation - Distributed and concurrent Erlang project with graphical display, running on 5 embedded computers

    Final project in Distributed & Concurrent Programming course

    Andre skabere
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  • Toaster

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    Complete redesign of the entire query testing system.
    We created a Haskell parser/compiler for our test description DSL and replaced thousands of lines of Python and dozens of files with easy to understand and debug generated code

    Andre skabere

  • Malicious traffic detection using traffic fingerprinting

    –

    Recipient of the 'Best Student Project' award for 2015, by the Communication Systems Engineering department at Ben Gurion University.

    We considered the problem of detecting malicious traffic in high bandwidth links. With the ever increasing bandwidth and traffic, deep packet inspection interferes with throughput and becomes computationally demanding. We developed a learning algorithm based on the well-known universal compression algorithm Lempel-Ziv 78. We built a proof-of-concept…

    Recipient of the 'Best Student Project' award for 2015, by the Communication Systems Engineering department at Ben Gurion University.

    We considered the problem of detecting malicious traffic in high bandwidth links. With the ever increasing bandwidth and traffic, deep packet inspection interferes with throughput and becomes computationally demanding. We developed a learning algorithm based on the well-known universal compression algorithm Lempel-Ziv 78. We built a proof-of-concept application that emulates a real-world situation and attempts to identify malware. Our algorithm builds a traffic fingerprint for well-known malware using only the time difference between packets. The algorithm then compares the fingerprint against unknown traffic. We studied the effectiveness of our method with real-world malicious traffic.

    Andre skabere
    Se projekt

Testresultat

  • TOEFL

    Resultat: 112

Sprog

  • English

    Modersmåls- eller tosprogsfærdighed

  • Hebrew

    Modersmåls- eller tosprogsfærdighed

  • Danish

    Begrænset praktisk færdighed

Anbefalinger, som du har modtaget

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