- Protect AI introduces MLSecOps Foundations, a free, four-part video training and certification program.
- Designed for AI users, developers, and security teams to secure AI and ML lifecycles.
- The program includes 20 modules, each averaging three minutes, covering AI security and prevention strategies.
- Participants earn certification upon completion, gaining skills in risk assessment, model security, and incident response.
- Led by cybersecurity veteran Diana Kelley, former security leader at Microsoft, IBM Security, and Symantec.
- Addresses real-world AI threats, referencing a recent attack on Ray, an open-source AI framework.
- Protect AI’s Sightline vulnerability database complements the initiative with early warnings on emerging AI threats.
Main AI News:
Protect AI Inc., a prominent player in AI and machine learning cybersecurity, has unveiled a free four-part video training and certification program called MLSecOps Foundations. This initiative is designed to help organizations embed security into their AI and ML lifecycles using the MLSecOps Framework, addressing the growing need for robust security practices in the AI landscape.
The MLSecOps Foundations program offers actionable insights for AI users, developers, and security teams on integrating AI security into their workflows. It ensures that companies are prepared to handle the evolving threats targeting AI and machine learning environments, providing them with a proactive defense strategy.
The curriculum is structured into four parts, consisting of 20 quick modules averaging three minutes each. These modules cover key areas of AI security, including identifying and mitigating risks, securing machine learning models, and employing the MLSecOps framework in real-world scenarios. Graduates of the course earn certification and acquire vital skills like conducting AI-specific risk assessments, auditing supply chains, and building incident response plans to safeguard their AI systems.
Diana Kelley, Protect AI’s Chief Information Security Officer and former cybersecurity leader at Microsoft, IBM Security, and Symantec, leads the program. Kelley emphasizes that AI/ML threats are no longer hypothetical, referencing a recent attack on Ray. This widely used AI framework has impacted multiple companies and their AI infrastructures.
Protect AI’s Sightline vulnerability database, launched earlier this year, further supports the company’s mission by offering early warnings and insights into emerging AI vulnerabilities. This tool provides crucial defense against new and existing threats, ensuring organizations can maintain secure AI and machine learning operations.
As the AI threat landscape evolves, the MLSecOps Foundations program equips teams with the knowledge and tools needed to proactively secure their AI systems, keeping pace with the dynamic nature of cybersecurity challenges.
Conclusion:
The launch of the MLSecOps Foundations program by Protect AI signals a growing recognition of the critical need for robust AI and machine learning security in the market. As AI integrates deeply into business operations, the associated risks become more tangible, with threats no longer theoretical. Protect AI addresses a critical market gap by equipping organizations with practical tools and frameworks to secure AI lifecycles. This move reflects a broader shift towards proactive security measures in AI, emphasizing that the future of the AI market will depend heavily on securing its infrastructure against evolving cyber threats. For businesses, investing in AI security will protect their operations and provide a competitive advantage in a rapidly digitizing landscape.
