Securing ML Systems Requires Understanding ML Technology

The key to ML Security is to understand the unique types of attacks possible and then to have the technology to differentiate attacks from legitimate use.

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Machine learning models are susceptible to manipulation and exploitation at every stage of their use from inception to operation. The ML system's ability to continually learn is paving the way for a new age of subtle and tailored attacks hidden behind human-mimicking conversations that will go widely undetected if the current ML security systems are not upgraded. Considering the inherent vulnerabilities of ML systems and the changing terrain of cybersecurity attacks, there is no doubt that machine learning attacks will soon become the next major threat vector in IT security.

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We understand the major vulnerabilities of ML Systems
We analyze ML System interactions to protect the system
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ML Security Technology in Action

Scanta’s VA Shield is the first product implementing our advanced ML Security Technology into a solution to protect Virtual Assistant Chatbots from Machine Learning attacks.