5 best practices to secure AI systems
Recent advancements in artificial intelligence have significantly expanded its capabilities, but this progress also introduces new security vulnerabilities that traditional frameworks are ill-equipped to handle. As AI systems become integral to critical operations, organizations must adopt a comprehensive, multi-layered defense strategy that emphasizes data protection, strict access controls, and continuous monitoring to mitigate risks associated with model theft, data breaches, and adversarial attacks. Key best practices include enforcing role-based access control and encrypting both AI models and training data to prevent unauthorized access and data leaks. Additionally, defending against model-specific threatssuch as adversarial inputs and model extractionrequires
