Machine Learning-Based Mobile Detection:
How Zimperium Provides Zero-Day Mobile Threat Defense

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Mobile devices now constitute the majority global web traffic. With billions of devices being used, a shortage of security talent, machine-speed attacks and efficient attacks, machine learning has become an absolute requirement for cyber security.

In contrast to traditional deterministic detection, Zimperium’s machine learning approach is perfectly suited for enterprise mobile security. Our machine learning engine, z9, analyzes system data to identify malicious behavior, and then creates sophisticated math models to enable on-device detection. z9 is not looking for a fingerprint of a known bad threat; it is identifying attacks, even those never seen before, by telltale actions that indicate a threat is occurring or imminent.

Since 2010, Zimperium has been feeding z9 with billions of data points from millions of devices, and z9 has been consistently learning and improving its accuracy. 

Since 2014, z9’s machine learning-based engine has detected every major mobile exploit on-device and without requiring updates.

z9’s Machine Learning-Based Engine

Download "Machine Learning-Based Mobile Detection: How Zimperium Provides Zero-Day Mobile Threat Defense" to learn more about the different approaches to cyber security and why Zimperium's machine learning-based detection is the superior approach for enterprise mobile security.

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