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Enterprise security personnel are defending a castle riddled with holes, secret passageways, and protected by ineffective barriers. These weak points are a consequence of poor quality security software, inferior hardware, and backdoors planted by malicious insiders. The end result is a begrudging acceptance that the attackers are winning the cybersecuirty war.
In order to keep up with modern attackers, security technologies need to evolve without relying on human intervention. That's where math and machine learning have the advantage. If we can objectively classify "good" files from "bad" based on mathematical risk factors, then we can teach a machine to make the appropriate decisions on these files in real time, allowing the "good" files to run, and the "bad" files to be quarantined BEFORE they can cause harm.
In this report, Cylance demonstrates that a math and machine learning approach to computer security will fundamentally change the way we understand, categorize and control execution of every file. We'll also discuss how our products leverage this approach and demonstrate just how different they are from every other security offering on the market.