Secure AI

Secure AI

Secure AI is a rapidly evolving field within artificial intelligence that focuses on developing AI systems that are robust, reliable, and resistant to various security threats and vulnerabilities. It encompasses a wide range of techniques and approaches aimed at ensuring the confidentiality, integrity, and availability of AI systems throughout their lifecycle, from training to deployment and operation. Secure AI addresses concerns such as data privacy, model integrity, adversarial attacks, and the potential misuse of AI technologies. It involves the application of cryptographic methods, secure multi-party computation, differential privacy, and other security measures to protect sensitive data and prevent unauthorized access or manipulation of AI models. Additionally, secure AI emphasizes the importance of explainable and interpretable AI models, allowing for greater transparency and accountability in decision-making processes. The field also explores the ethical implications of AI security, including the responsible development and deployment of AI systems that align with societal values and mitigate potential risks and biases. As AI becomes increasingly integrated into critical domains such as healthcare, finance, and national security, the development of secure AI practices becomes paramount to ensure the trustworthiness and reliability of these systems.

adversarial attacks, cryptographic methods, data privacy, differential privacy, explainable AI, interpretable AI, model integrity, secure multi-party computation

— Robert Anderson

CITATION : "Robert Anderson. 'Secure AI.' Design+Encyclopedia. https://design-encyclopedia.com/define/secure-ai?E=432972 (Accessed on October 14, 2026)"