基于深度学习的IDS可信安全模型

K. Makdi, Frederick T. Sheldon, A. A. Hussein
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引用次数: 2

摘要

目前,云计算正成为IT公司的首选,因为它提供了灵活性和按使用付费的服务。尽管如此,隐私和安全问题是成功部署云计算的重大挑战,因为云计算的分布式和开放架构容易受到入侵。云计算的开放和分布式结构对潜在的网络罪犯越来越有吸引力。传统的入侵检测系统由于其开放性,在云计算环境下大多是无效的。本文研究了新型入侵检测系统的部署,其中包括基于信任的自适应安全模型,通过深度学习进行入侵检测。
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Trusted Security Model for IDS Using Deep Learning
Contemporarily, cloud computing is becoming the most preferred choice for IT firms because it offers flexibility and pay-per-use services. Nonetheless, privacy and security issues are significant challenges in the successful deployment of cloud computing attributed to its distributed and open architectures that are exposed to intrusions. The open and distributed structures of cloud computing are increasingly appealing to potential cybercriminals. Conventional intrusion detection systems are largely ineffective in the cloud computing environment because of their openness. This paper examines the deployment of novel intrusion detection systems involving a trust-based adaptive security model for intrusion detection through deep learning.
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