Abstract:Although artificial intelligence technology has been widely used in the field of public security and national defense security, the security of these intelligent systems faces great challenges. How to effectively, comprehensively, and deeply test the security of intelligent systems has become a crucial problem to enhance the security of current intelligent systems. In recent years, researchers and institutions attached great importance to the security of intelligent systems, carried out a large number of studies on security testing theories and methods, and issued a large number of relevant policy documents. Aiming at the security problems in intelligent systems, this research elaborates the theory and method of security testing from the perspective of the full life cycle ideology. Firstly, it explains the characteristics, security connotation and security mechanism of intelligent system; Then, combining the critical life cycle stages of model training, model inference, and model deployment, it elaborates the security challenges faced by the intelligent system and the testing theory and methods in detail; Finally, it clarifies the way to build an security test support hierarchy from the perspective of standards and platforms, analyzes the intelligent system security test cases under typical scenarios of automatic driving, and gives the prospects of the future security testing. It concludes that the construction of intelligent system security testing theory and method system can effectively avoid potential risks and quality defects; it is a basic path to achieve an interpretable and trustworthy artificial intelligence algorithm and is of great significance to ensure the safety, reliability and controllability of artificial intelligence technology.