Adversarial attacks on machine learning (ML) models are growing in intensity, frequency and sophistication with more enterprises admitting they have experienced an AI-related security incident. AI's ...

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With machine learning becoming increasingly popular, one thing that has been worrying experts is the security threats the technology will entail. We are still exploring the possibilities: The ...

Much of the anti-adversarial research has been on the potential for minute, largely undetectable alterations to images (researchers generally refer to these as “noise perturbations”) that cause AI’s ...

Machine learning (ML) and artificial intelligence (AI) are essential components in modern and effective cybersecurity solutions. However, as the use of ML and AI in cybersecurity is increasingly ...

As a cloud operations professional focusing on machine learning (ML), my work helps organizations grasp ML systems' security challenges and develop strategies to mitigate risks throughout the ML ...

The extraordinary advances in machine learning that drive the increasing accuracy and reliability of artificial intelligence systems have been matched by a corresponding growth in malicious attacks by ...

In May 2016, Microsoft introduce a chatbot on Twitter, dubbed "Tay," that attempted to hold conversations with users and improve its responses through machine learning (ML). A coordinated attack on ...

The adoption of DevSecOps has reshaped cybersecurity, but DevSecOps isn’t enough to keep all software safe. The addition of artificial intelligence (AI) and machine learning (ML), for example, has ...