Cloud computing environments face multiple security threats, including DDoS attacks and SQL injection. Traditional security protection methods are lagging in responding to new types of attacks. This paper proposes an adaptive security protection method based on deep learning, constructing a multi-layered protection architecture and verifying it in a real-world business environment. The system achieves a detection accuracy of 97.3%, an average response time of 18ms, and an availability of 99.999%. Experimental results show that this method has significant advantages in detection accuracy, response efficiency, and resource utilization, providing a new solution for cloud computing security protection.
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Wang et al. (2025) studied this question.
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