从全网角度检测和缓解NDN中复杂的兴趣泛洪攻击

Guang Cheng, Lixia Zhao, Xiaoyan Hu, Shaoqi Zheng, Hua Wu, Ruidong Li, Chengyu Fan
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引用次数: 9

摘要

兴趣泛洪攻击(IFA)是命名数据网络(NDN)的主要安全威胁之一。现有的对策大多是使攻击者附近的中间路由器能够独立检测攻击,并考虑攻击者以恒定且较高的速率直接发送恶意兴趣的典型攻击场景。此外,他们在执行现有的中间路由器防御措施时也可能会扼杀合法利益,因为他们仍然难以区分攻击者发布的利益和合法消费者发布的利益。相反,这项工作的目标是一个更复杂的攻击场景,攻击者以相对较低的速度开始攻击,但逐渐加速,以保持受害者的未决利息表(未决利息表)增加,最终耗尽合法消费者的PIT资源。对于中间路由器来说,独立且及时地检测到这种复杂的IFA是比较困难的。为了解决这一问题,我们提出了一种从网络全局角度检测复杂IFA的机制。中央控制器通过攻击者发送的第一跳路由器的异常信息报告,收集整个网络的整体状态,对网络是否发生IFA进行全面、快速的判断。确定IFA后,可以直接定位攻击源,在不限制合法权益的情况下,防止恶意权益进入网络。我们进行了一项实验研究,以评估所提出机制的性能,并探索攻击检测算法在接入路由器上的参数设置。实验结果验证了我们的机制可以在不限制合法消费者请求的情况下及时检测和缓解复杂的IFA。
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Detecting and Mitigating A Sophisticated Interest Flooding Attack in NDN from the Network-Wide View
Interest Flooding Attack (IFA) is one of the main security threats for the Named Data Networking (NDN). Most of its existing countermeasures enable intermediate routers near the attackers to independently detect the attack and consider the typical attack scenario in which attackers directly send malicious Interests at a constant and relatively high rate. Moreover, they may also throttle legitimate Interests when enforcing the existing defence measures at intermediate routers as it is still difficult for them to distinguish the Interests issued by attackers from those issued by legitimate consumers. Instead, this work aims at a more sophisticated attack scenario in which attackers start the attack at a relatively lower rate but gradually speed up to keep the Pending Interest Tables (PITs) of the victims increasing to finally deplete the PIT resources for legitimate consumers. It is relatively difficult for intermediate routers to independently and timely detect such a sophisticated IFA. To solve this problem, we propose a mechanism to detect the sophisticated IFA from the network-wide view. A central controller monitors the network and makes a comprehensive and prompt decision on whether there is an ongoing IFA based on the overall state of the whole network collected from the abnormity information reports sent by the first-hop routers of attackers. Attack sources can be directly located after an IFA is determined and then the malicious Interests can be prevented from entering the network without throttling legitimate Interests. We conduct an experimental study to evaluate the performance of the proposed mechanism and explore the parameter settings of the attack detection algorithm at access routers. The experimental results validate that our mechanism can timely detect and mitigate the sophisticated IFA without throttling requests from legitimate consumers.
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Integrating In-Network Computing for Secure and Efficient Cascaded Delivery in DTNs Keep Forwarding Path Freshest in VANET via Applying Reinforcement Learning Publisher's Information [Title page iii] Detecting and Mitigating A Sophisticated Interest Flooding Attack in NDN from the Network-Wide View
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