Machine learning set to Impact Online Security

Artificial Intelligence

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Technology moves swiftly. Nowhere is that more accurate than in the current state of machine learning.

A lack of awareness of security issues in the C-Suite and among employees is part of the problem, but the major cause is the enormous complexity of modern infrastructure deployments and the data generated by corporate and government networks. Finding security breaches is incredibly difficult.

Online criminals want to remain hidden — if they’re discovered, it’s game over. They invest significant resources into hiding their presence, but it’s impossible for them to hide completely. There are always tell-tale network and usage patterns. But those patterns are constantly changing and obscured within massive quantities of genuine user interactions.

With reams of data being generated and transferred over networks, cybersecurity experts will have a hard time monitoring everything that gets exchanged — potential threats can easily go unnoticed. Hiring more security experts would offer a temporary reprieve, but the cybersecurity industry is already dealing with a widening talent gap, and organizations and firms are hard-pressed to fill vacant security posts.

The solution might lie in machine learning, the phenomenon that is transforming an increasing number of industries and has become the buzzword in Silicon Valley.

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