VentureBeat

Adversarial attacks in machine learning: What they are and how to stop them

Adversarial machine learning, a technique that attempts to fool models with deceptive data, is a growing threat in the AI and machine learning research community. The most common reason is to cause a ...
Infosecurity-magazine.com

#InfosecurityEurope: Preparing for Adversarial Machine Learning Attacks

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 ...
IT Business Edge

Adversarial Machine Learning: Combating Data Poisoning

The fields of machine learning (ML) and artificial intelligence (AI) have seen rapid developments in recent years. ML, a branch of AI and computer science, is the process through which computers can ...
AFCEA

Cracking the Code on Adversarial Machine Learning

The vulnerabilities of machine learning models open the door for deceit, giving malicious operators the opportunity to interfere with the calculations or decision making of machine learning systems.
Forbes

AI Ethics Tempted But Hesitant To Use AI Adversarial Attacks Against The Evils Of Machine Learning, Including For Self-Driving Cars

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. It is widely accepted sage wisdom to garner as much as you can ...
Nextgov

NIST releases finalized guidelines on protecting AI from attacks

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 ...
VentureBeat

MLsec could be the answer to adversarial AI and machine learning attacks

VentureBeat presents: AI Unleashed - An exclusive executive event for enterprise data leaders. Network and learn with industry peers. Learn More With research showing that private investment in ...
Nature

Adversarial Attacks in Deep Learning for Wireless Communication

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 ...
The National Law Review

NIST Finalizes Cyber Attack Guidance for Adversarial Machine Learning

We collaborate with the world's leading lawyers to deliver news tailored for you. Sign Up for any (or all) of our 25+ Newsletters. Some states have laws and ethical rules regarding solicitation and ...
EurekAlert!

Discovery of universal adversarial attacks for quantum classifiers

Artificial intelligence has achieved dramatic success over the past decade, with the triumph in predicting protein structures marked as the latest milestone. At the same time, quantum computing has ...
National Academies of Sciences%2c Engineering%2c and Medicine

Robust Machine Learning Algorithms and Systems for Detection and Mitigation of Adversarial Attacks and Anomalies: Proceedings of a Workshop

This activity was supported by Contract 2014-14041100003-019 with the Office of the Director of National Intelligence. Any opinions, findings, conclusions, or recommendations expressed in this ...