Outsmarting Malware: Why Machine Learning Bests Traditional AV

Provided by Juniper Networks

Category Malware

Type White Paper

Length 7

Publish Date August 15 2017

Date posted August 15 2017


Malware writers are always a step ahead of traditional security solutions, creating threats that behave differently from system to system, day to day, and year to year. For example, some infections now disguise or even partially encrypt themselves so they don’t match known signatures in the malware databases.  This paper discusses a modern approach to cybersecurity that uses adaptable machine learning algorithms combined with several anti-malware technologies to find and foil advanced threats.

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