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 ...

We are witnessing a rapid advancement of AI and its impact across various industries. However, with great power comes great responsibility, and one of the emerging challenges in the AI landscape is ...

The final guidance for defending against adversarial machine learning offers specific solutions for different attacks, but warns current mitigation is still developing. NIST Cyber Defense The final ...

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 ...

The study analyzed 121 short videos as part of a small dataset to distinguish between truthful and deceptive conversations. Scientists have revealed that Convolutional Neural Networks (CNNs), a type ...

Adversarial AI exploits model vulnerabilities by subtly altering inputs (like images or code) to trick AI systems into misclassifying or misbehaving. These attacks often evade detection because they ...

The study analyzed 121 short videos as part of a small dataset to distinguish between truthful and deceptive conversations. Credit: Expert Systems with Applications (2025). DOI: The research examined ...