The study, titled Conditional Adversarial Fragility in Financial Machine Learning under Macroeconomic Stress, published as a ...

The field of adversarial attacks in natural language processing (NLP) concerns the deliberate introduction of subtle perturbations into textual inputs with the aim of misleading deep learning models, ...

Artificial intelligence (AI) safety has turned into a constant cat-and-mouse game. As developers add guardrails to block ...

In a new proof-of-concept, endpoint security provider Morphisec showed that the Exploit Prediction Scoring System (EPSS), one of the most widely used frameworks for assessing vulnerability exploits, ...

Your security tools say everything’s fine, but attackers still get through. Despite years of investment in firewalls, endpoint protection, SIEMs, and other layered defenses, most organizations still ...

In the research, they analyze the relation of adversarial transferability and output consistency of different models, and observe that higher output inconsistency tends to induce lower transferability ...

Red teaming is a powerful way to uncover critical security gaps by simulating real-world adversary behaviors. However, in practice, traditional red team engagements are hard to scale. Usually relying ...

Lily is a Senior Editor at BizTech Magazine. She follows tech trends, thought leadership and data analytics. Todd Felker, executive healthcare strategist at CrowdStrike, said the rise of social ...

Let’s start by working our way back. To set the scene: You and your team successfully repelled a ransomware attack. You stop it before it spreads, disrupts your work or steals your data. You avoid the ...