Facing strict privacy laws, telcos use AI-generated synthetic data as a compliant workaround to train ML models without exposing sensitive customer information.

What’s the first thing you think of when you hear about ai security threats and vulnerabilities? If you’re like most people, your mind probably jumps to Large Language Model (LLM) ...

The global maritime industry has long been the arterial system of the world economy, responsible for over 90% of global trade. For ...

Threat actors are operationalizing AI to scale and sustain malicious activity, accelerating tradecraft and increasing risk for defenders, as illustrated by recent activity from North Korean groups ...

Sasha S. Rao and Todd M. Hopfinger of Sterne, Kessler, Goldstein & Fox PLLC discuss challenges in meeting patent law's disclosure requirements for inventions involving artificial intelligence, ...

Two-thirds of security incidents traced back to identity-related weaknesses as attackers move faster and strike after hours ...

Cybersecurity has always been a game of adaptation, but the emergence of AI-driven polymorphic threats is accelerating that arms race.

Adversaries are hijacking AI technology for their own purposes, generating deepfakes, creating clever phishing lures, and launching novel types of advanced attacks. They are also targeting AI systems ...

Abstract: Deep neural networks are increasingly used in image processing tasks. However, deep learning models often show vulnerability when facing adversarial attacks. Active defense is an important ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this work, we introduce auxiliary discriminator sequence generative adversarial ...