cPAID envisions to develop a cloud-based, platform-agnostic defense framework to protect AI systems from adversarial attacks and cyber threats. As AI becomes more integrated into critical sectors—ranging from autonomous vehicles to smart medical devices—it also faces growing security risks such as data poisoning, evasion attacks, and model theft.

cPAID will enhance AI security and resilience by combining AI-driven intrusion detection, risk management, and privacy-by-design principles. It will introduce the MLPrivSecOps methodology, which ensures AI models are built with security, privacy, and robustness from the ground up. Additionally, Generative AI will be leveraged to simulate adversarial attacks, strengthening AI defenses before deployment.

Integrating context-awareness, explainable AI (XAI), and cybersecurity best practices, cPAID aims to create a trustworthy AI ecosystem. Ultimately, cPAID aims to set new standards for AI security certification, ensuring AI applications remain reliable and secure.