Data Security Assessment Method Based on Penetration Testing

In view of the increasingly serious information security threats in the context of the rapid development of Internet technology, this article adopts a data security assessment method based on penetration testing, aiming to improve the network security protection capabilities of enterprises and institutions and prevent potential intrusion and data leakage risks. Firstly, this article establishes a comprehensive security assessment framework that includes information collection, vulnerability analysis. Secondly, this article combines artificial intelligence technology and utilizes artificial neural networks and SVM (Support Vector Machine) algorithms for vulnerability risk assessment and ranking. The research results show that the proposed method achieves a critical vulnerability detection rate of 85% in simulating enterprise network environments, with a detection response time of about 0.15 seconds and a fast response to threats. The dynamic and real-time security protection system constructed not only accurately identifies potential security risks in the system, but also significantly improves the efficiency and accuracy of data security assessment.