Cloud Security, AI Security, and Quantum-Ready Cyber Resilience: A Conversation with Ankit Gupta, Cybersecurity and AI Security Leader [English]

In an insightful interview, Ankit Gupta discusses the evolving landscape of cybersecurity, emphasizing the importance of cloud security, AI governance, and preparing for quantum computing challenges. He advocates for proactive, resilient architectures that prioritize ethical practices and continuous adaptation to safeguard critical data in an increasingly complex digital environment.

Main attacks on artificial intelligence models: threats, examples, and cybersecurity challenges [Spanish]

Artificial intelligence models are increasingly targeted by malicious actors, posing significant cybersecurity risks. Attacks can range from intellectual property theft to algorithm manipulation. Ensuring the security of these systems requires comprehensive measures, including data validation and protection of APIs, to keep pace with evolving technological threats.

Interview with Google Cloud Security Chief: Gemini TPU is optimal for AI security [Korean]

In an interview, Mark Johnstone, Google Cloud’s security lead for the Asia-Pacific region, emphasized the company’s commitment to AI-driven cybersecurity. He highlighted the importance of collaboration with governments and startups to enhance security measures, showcasing innovations like the Gemini AI model and the Secure AI framework to protect users effectively.

Identity as the new perimeter: National Oilwell Varco’s approach to stopping the 79% of attacks that are malware-free [English]

National Oilwell Varco (NOV) is transforming its cybersecurity with a Zero Trust architecture, achieving a 35-fold reduction in security incidents. CIO Alex Philips emphasizes the importance of identity defenses and AI integration, highlighting the need for continuous verification and proactive measures against the rising threat of credential-based attacks.

A growing role for red teams in defending AI systems | Report [Egypt]

The increasing complexity of artificial intelligence systems necessitates specialized red teams to identify vulnerabilities. Unlike traditional cybersecurity, these teams must adapt to dynamic threats, employing innovative strategies to secure AI operations. Collaboration among multidisciplinary experts is essential to enhance defenses and ensure robust protection against unique AI-related risks.

Wordpress Social Share Plugin powered by Ultimatelysocial
LinkedIn
Share
Instagram
RSS