Nov 8, 2025 · This article explores how adversarial AI works, why model poisoning is so difficult to detect, and what organizations can do to defend against these emerging threats.

Aug 16, 2023 · This collective body of research illustrates the ongoing arms race in AI cybersecurity, spotlighting both the challenges and innovative solutions in the battle against …

Jun 11, 2025 · Large language models can become compromised when their training datasets are intentionally poisoned by malicious attackers. CyLab researchers have demonstrated that …

Abstract—This paper investigates the critical issue of data poisoning attacks on AI models, a growing concern in the ever-evolving landscape of artificial intelligence and cybersecurity.

Jan 4, 2024 · AI systems can malfunction when exposed to untrustworthy data, and attackers are exploiting this issue. New guidance documents the types of these attacks, along with …

Aug 22, 2025 · Explore the growing threat of model poisoning, a cyberattack where machine learning models are manipulated, and how your organization can defend against it. It’s no …

Mar 26, 2024 · Depending on the attacker’s goals and capabilities, this report identified the four most common types of attacks: evasion, poisoning, privacy attacks (that affect both Predictive …

Learn how to protect AI models from poisoning and evasion attacks. Explore data sanitization, adversarial training, and robust defense strategies with practical code samples in Python.

This paper assesses the efficacy of adversarial attacks on decision trees, SVM, DNN, and XGBoost models, as well as the performance of defense mechanisms for improving model …

Sep 29, 2025 · Discover the critical importance of defending AI models against adversarial attacks in the cybersecurity landscape. Learn about six key attack categories and their consequences …