Adversarial machine learning, a technique that attempts to fool models with deceptive data, is a growing threat in the AI and machine learning research community. The most common reason is to cause a ...
The integration of deep learning techniques into wireless communication systems has catalysed notable advancements in tasks such as modulation classification and spectrum sensing. However, the ...
A new report has revealed that open-weight large language models (LLMs) have remained highly vulnerable to adaptive multi-turn adversarial attacks, even when single-turn defenses appear robust. The ...
SAN FRANCISCO, March 19, 2026 (GLOBE NEWSWIRE) -- Votal AI, the AI-native security platform purpose-built for agentic AI systems and founded by cybersecurity veterans Bobby Gupta (CEO) and Jyotirmoy ...
The easy availability of highly effective phishing-as-a-service platforms has ensured the technique's ongoing relevancy despite its provenance dating to the internet's early days. See Also: Why ...
Rivals OpenAI, Anthropic PBC, and Alphabet Inc.’s Google have begun working together to try to clamp down on Chinese ...
BreachLock, a global leader in offensive security, today announced it has been named a representative vendor in the 2026 ...
IFAP generates adversarial perturbations using model gradients and then shapes them in the discrete cosine transform (DCT) domain. Unlike existing frequency-aware methods that apply a fixed frequency ...
Executive summary Forest Blizzard, a threat actor linked to the Russian military, has been compromising insecure home and ...
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