Page 75 - Cyber Defense eMagazine - November 2017
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A DIFFERENT APPROACH THAT INCREASES ACCURACY

               To  maximize  coverage  and  accuracy,  the  approach  to  machine  learning  we  take  at  Barkly
               involves  nightly  training  of  our  models  (which  keeps  protection  up-to-date)  as  well  as  the
               creation of organization-specific models trained against each company’s unique software profile.
               Not only does that allow our models to be more current and responsive to the newest threats, it
               also allows them to be less reactive to the legitimate goodware deployed in each environment.

               Here’s how it works: Each night, we collect thousands of samples of new malicious software,
               and  we  combine  those  samples  with  up-to-the-minute  data  on  the  known-good  software
               organizations are running. We then re-train and redistribute the  updated models, which have
               been tailored and optimized specifically for each organization. Thanks to that cadence, we’re
               able to provide more accurate, maximized protection that maintains its strength over time.

               We  believe  this  new,  responsive  approach  represents  an  exciting  step  forward  in  the  way
               security providers can apply machine learning. But the truth is we still have a very long way to
               go before we tap the technology’s full potential. As adoption of machine learning becomes more
               prevalent we’re eagerly anticipating more breakthroughs that tip the scales against attackers.

               About the Author

                                             Sarosh Petkar is a BS/MS student of the RIT Computing Security
                                             department.  He  is  currently  working  as  a  Malware  Analyst  at
                                             Barkly,  the  Endpoint  Protection  Platform  that  delivers  the
                                             strongest protection with the fewest false positives and simplest
                                             management.
                                             His interests include reverse engineering, network security, and
                                             cryptography.


                                             He can be reached online at [email protected].




















                   75    Cyber Defense eMagazine – November 2017 Edition
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