利用INT数据对物联网生态系统进行网络内DDoS检测和缓解

Pub Date : 2023-01-01 DOI:10.36244/icj.2023.5.8
Gereltsetseg Altangerel, M. Tejfel
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引用次数: 0

摘要

由于物联网(IoT)设备的功能有限和多样性,为这些设备实施强大而统一的安全标准是一项挑战。此外,易受攻击的物联网设备超出了网络的控制范围,这一事实使它们容易受到攻击,并被用作机器人或僵尸网络的一部分,导致最近涉及这些设备的攻击激增。我们在软件定义网络(SDN)环境中,利用带内网络遥测(INT)数据,在可编程数据平面上提出了一种实时物联网异常检测和缓解解决方案来解决这个问题。据我们所知,这是第一次在可编程数据平面上使用INT数据检测物联网攻击的实验。根据我们的性能评估,我们提出的方法的检测延迟远低于以往的分布式拒绝服务(DDoS)研究结果,并且检测精度同样高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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In-network DDoS detection and mitigation using INT data for IoT ecosystem
Due to the limited capabilities and diversity of Internet of Things (IoT) devices, it is challenging to implement robust and unified security standards for these devices. Additionally, the fact that vulnerable IoT devices are beyond the network’s control makes them susceptible to being compromised and used as bots or part of botnets, leading to a surge in attacks involving these devices in recent times. We proposed a real-time IoT anomaly detection and mitigation solution at the programmable data plane in a Software-Defined Networking (SDN) environment using Inband Network telemetry (INT) data to address this issue. As far as we know, it is the first experiment in which INT data is used to detect IoT attacks in the programmable data plane. Based on our performance evaluation, the detection delay of our proposed approach is much lower than the results of previous Distributed Denial-of-Service (DDoS) research, and the detection accuracy is similarly high.
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