Brain-Inspired Neuromorphic Cybersecurity System Detects ”Bad Apples” 100X Faster

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June 5, 2017 | Originally published by Date Line: June 5 on

Cybersecurity is critical—for national security, corporations and private individuals. Sophisticated cybersecurity systems excel at finding “bad apples” in computer networks, but they lack the computing power to identify the threats directly.

Instead, they look for general indicators of an attack; call them “apples.” Or the system flags very specific patterns, such as “bad Granny Smith apples” or “bad Red Delicious apples.”

These limits make it easy for new species of “bad apples” to evade modern cybersecurity systems. And security analysts must sort the real dangers from false alarms, such as the nonsense phrase “forbad applesauce.”

The Neuromorphic Cyber Microscope, designed by Lewis Rhodes Labs in partnership with Sandia National Laboratories, directly addresses this limitation. Due to its brain-inspired design, it can look for the complex patterns that indicate specific “bad apples,” all while using less electricity than a standard 60-watt light bulb.

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