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 ...
The Artificial Intelligence and Machine Learning (“AI/ML”) risk environment is in flux. One reason is that regulators are shifting from AI safety to AI innovation approaches, as a recent DataPhiles ...
The integration of deep learning techniques into wireless communication systems has catalysed notable advancements in tasks such as modulation classification and spectrum sensing. However, the ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Security leaders’ intentions aren’t matching up with their actions to ...
The rise of artificial intelligence has rendered portions of your current cybersecurity playbook obsolete. Unless Chief Information Security Officers ...
The National Institute of Standards and Technology (NIST) has published its final report on adversarial machine learning (AML), offering a comprehensive taxonomy and shared terminology to help ...
Over the past year, I've been working on a challenge that faces every organization implementing Zero Trust: how do you manage ...
With the EU's AI Act coming into force imminently, those designing, developing, and/or deploying AI will need to start getting to grips with the myriad of new obligations, including new cyber security ...
Harshith Kumar Pedarla explores using GANs to simulate network attacks. Synthetic data augmentation improves detection scores ...
In a landmark move, the US National Institute of Standards and Technology (NIST) has taken a new step in developing strategies to fight against cyber-threats that target AI-powered chatbots and ...
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