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 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 ...

The Splunk Threat Research Team is releasing v4.0 of Splunk Attack Range, an open source project that allows security teams to spin up a detection development environment to emulate adversary behavior ...

Cyber-incident attribution gets a lot of attention, for good reasons. Identifying the actor(s) behind an attack enables taking legal or political action against the adversary and helps cybersecurity ...

Labeling adversary activity with ATT&CK techniques is a tried-and-true method for classifying behavior. But it rarely tells defenders how those behaviors are executed in real environments.