ESET's road to Augur

Discussion in 'ESET' started by BoraMurdar, Jun 20, 2017.

  1. BoraMurdar

    BoraMurdar Super Moderator
    Staff Member

    Aug 30, 2012
    Doctor of medicine
    Windows 10
    Full article
    Machine learning by ESET: The road to Augur

    At ESET we love ancient history – the company is named after an Egyptian goddess after all – so that was naturally the place we looked for when it came to naming our machine learning engine. In Ancient Rome, Augur was a term used for religious officials who observed natural signs and interpreted these as an indication of divine approval or disapproval of a proposed action. The analogy with cybersecurity is not hard to draw, but in contrast with the alchemy-natured augurs back then, our Augur bases its decisions on science, mathematics and previous experience.
  2. Huchim

    Huchim Level 4

    Oct 17, 2015
    Windows 8.1
    So, it's already included in ESET's products? or how can see it in action? it's a detection name maybe? for example as far as I know norton use machine learning on some detections and name it
    AtlBo likes this.
  3. mekelek

    mekelek Level 22

    Feb 24, 2017
    Windows 10
    ESET does this for all executed application, hence it has such a good static detection.
  4. Huchim

    Huchim Level 4

    Oct 17, 2015
    Windows 8.1
    Yeah and I think that's why fails if not catch something after a static detection. Since V7 always have failed detecting a common worm I think that spreads for USB on my region
    ravi prakash saini and AtlBo like this.
  5. Korea

    Korea Level 1

    Jan 11, 2017
  6. ravi prakash saini

    Apr 22, 2015
    Windows 10
    good flow chart but in recent times they are finding it hard to make it work in practical
  7. Parsh

    Parsh Level 24
    Trusted AV Tester

    Dec 27, 2016
    7 Islands of Bombay
    Windows 10
    #7 Parsh, Jun 21, 2017
    Last edited: Jun 21, 2017
    That's an interesting consolidation of the algorithms and AI approaches proven to be effective till now. No doubt that explains their powerful detection.
    @Huchim they have been using ML techniques since years and this seems to be their new AI project or a rebranding of their project, implementing the best of Deep Learning and Classification algorithms they've found to be useful.
    Nice share :)
    Sunshine-boy likes this.
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