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 ...
HHS

AI Deception Is a Story, Not Just Code

This shift needs a radically new approach, one rooted in cognitive defense, not just technical controls, said Perry Carpenter, chief human risk management strategist at KnowBe4. "The battlefield is of ...
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 ...
Hosted on MSN

Machine learning methods are best suited to catch liars, according to science of deception detection

Scientists have revealed that Convolutional Neural Networks (CNNs), a type of deep learning algorithm, demonstrate superior performance compared to conventional non-machine learning approaches when ...