GitHub

adversarial-machine-learning

Explore adversarial attacks on traffic sign recognition models and evaluate defenses using adversarial training. Includes FGSM, PGD, BIM attacks, and robust model comparison through an interactive ...
IEEE

On the Economics of Adversarial Machine Learning

Abstract: Given the widespread deployment of machine learning algorithms, the security of these algorithms and thus, the field of adversarial machine learning gained popularity in the research ...
Hacker

64 Stories To Learn About Machine Learning Tutorials

Lets geek out. The HackerNoon library is now ranked by reading time created. Start learning by what others read most. Lets geek out. The HackerNoon library is now ranked by reading time created. Start ...
Techopedia

Leveraging Adversarial Machine Learning for Enhanced Cybersecurity

Adversarial machine learning is crucial for safeguarding ML models against attacks. Techniques like adversarial training, defensive distillation, and ensemble methods enhance resilience. As ML becomes ...
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 ...
IEEE

Adversarial Machine Learning in Wireless Communications Using RF Data: A Review

Abstract: Machine learning (ML) provides effective means to learn from spectrum data and solve complex tasks involved in wireless communications. Supported by recent advances in computational ...