Cloud computing has changed online communities in three dimensions, which are scalability, adaptability and reduced overhead. But there are serious security concerns which are brought about by its distributed and multi-tenant characteristics. The old methods of detecting and reacting to threats which are mostly reliant on fixed signatures, predefined rules and human operators are becoming less and less effective even in the advanced stages of cyberattacks of cloud infrastructures. The recent trend in the field of addressing these limitations is the creation of technologies of artificial intelligence (AI). The strategies allow independent protection, anomaly detection, and real-time analysis with references to using deep learning, machine learning, and reinforcement learning. Through imbuing AI with a constantly-learning feature, it enables the intrusion detection system to be more accurate and generate a lesser number of false positives and it also enables the possibility of adaptive and predictive security. The fusion of large-scale language models with efficient orchestration platforms contributes to reacting to the arising threats with a quicker and more precise response. This allows automatic control over incidences, self-healing network, and defense mechanisms on a policy basis. Considering the current detection and response methods, this discussion assesses their strengths and weaknesses and outlines key issues such as data privacy, adversarial machine learning and integration complexity in the context of AI-based cloud security. These results suggest the future application of AI to support autonomous, scalable and active cloud security operations.

翻译：云计算在可扩展性、适应性和降低开销三个维度上改变了在线社区。然而，其分布式和多租户特性也带来了严重的安全隐患。传统的威胁检测与响应方法主要依赖固定特征库、预定义规则和人工操作，在云基础设施面临高级网络攻击时正变得越来越低效。近年来，为应对这些局限性，人工智能（AI）技术在该领域的发展已成为重要趋势。通过运用深度学习、机器学习和强化学习，这些策略能够实现自主防护、异常检测和实时分析。通过赋予AI持续学习的能力，可使入侵检测系统提升准确性、降低误报率，并实现自适应与预测性安全。大规模语言模型与高效编排平台的融合，有助于对新兴威胁作出更快速、更精准的响应。这使得基于策略的事件自动控制、自愈网络和防御机制成为可能。本文在评估现有检测与响应方法优劣的基础上，剖析了AI驱动云安全中的关键问题，包括数据隐私、对抗性机器学习以及系统集成复杂性。研究结果指明了未来AI在支持自主、可扩展和主动式云安全运维中的应用方向。