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Due to the increasing role of cloud computing in the growth of trustable digital services, secure and efficient solutions will be a must in the mitigation of cyber risks. This paper presents an approach to the enhancement of cloud security through the application of deep learning, focusing on Artificial Neural Networks. Moderate segments of ANN algorithms have been performed that are Levenberg–Marquardt(LM), Scaled Conjugate Gradient(SCG) and Bayesian Regularization(BR), to build an enhanced threat detection system which has the capability of detecting highly complex attacking patterns in the cloud.The paper also looks at the problem of various types of cyber threat detection–malware, phishing, distributed denial of service (DDos) attacks etc. Finally, it can be concluded that employing the knowledge of ANN, and other, deep learning approaches, can facilitate the development of persistent cyber defense structures in the cloud. The research shows how ANN models can contribute to a faster and easier detection of new, unclassified threats, therefore increasing the overall security of cloud related activities.

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Enhancing Cloud Security with Deep Learning—An ANN Approach for Cyber Threat Detection

  • 会议论文

  • 发表日期：

    2026年

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  • Mothe Sathyam Reddy,
  • Gattu Thanuja,
  • Rama Krishna Eluri,
  • Bojja Sobharani,
  • Thalapaneni Suma Durga,
  • Dodda Venkata Reddy,
  • Moturi Sireesha

摘要

Due to the increasing role of cloud computing in the growth of trustable digital services, secure and efficient solutions will be a must in the mitigation of cyber risks. This paper presents an approach to the enhancement of cloud security through the application of deep learning, focusing on Artificial Neural Networks. Moderate segments of ANN algorithms have been performed that are Levenberg–Marquardt(LM), Scaled Conjugate Gradient(SCG) and Bayesian Regularization(BR), to build an enhanced threat detection system which has the capability of detecting highly complex attacking patterns in the cloud.The paper also looks at the problem of various types of cyber threat detection–malware, phishing, distributed denial of service (DDos) attacks etc. Finally, it can be concluded that employing the knowledge of ANN, and other, deep learning approaches, can facilitate the development of persistent cyber defense structures in the cloud. The research shows how ANN models can contribute to a faster and easier detection of new, unclassified threats, therefore increasing the overall security of cloud related activities.