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A novel deep learning model for detection of denial of service attacks in HTTP traffic over internet

机译:互联网HTTP流量拒绝服务攻击的新型深度学习模型

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摘要

The technological advancements in internet and mobile communications bring new dimension to the usage of internet applications and services. The accessibility to the enhanced services is intentionally blocked by the denial of service attacks. This paper proposes a novel deep learning classification model to detect the denial of service attacks in application layer for different network environments, such as wired network, ad hoc network and mobile ad hoc network. The simulation results illustrate that the performance of the proposed deep learning model is proficiently improved compared to existing bio-inspired and machine learning models in terms of detection accuracy and classification metrics.
机译:互联网和移动通信技术进步为互联网应用程序和服务带来了新的维度。通过拒绝服务攻击,有意阻止增强服务的可访问性。本文提出了一种新的深度学习分类模型,可以检测不同网络环境的应用层中的拒绝服务攻击,例如有线网络,临时网络和移动临时网络。仿真结果表明,与检测准确性和分类指标的现有生物启发和机器学习模型相比,所提出的深度学习模型的性能熟练地改善。

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