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增强对体积型分布式拒绝服务攻击的缓解:一种混合现场可编程门阵列/软件过滤数据路径。

Enhancing Mitigation of Volumetric DDoS Attacks: A Hybrid FPGA/Software Filtering Datapath.

作者信息

Salopek Denis, Mikuc Miljenko

机构信息

Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia.

出版信息

Sensors (Basel). 2023 Sep 3;23(17):7636. doi: 10.3390/s23177636.

DOI:10.3390/s23177636
PMID:37688092
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10490799/
Abstract

The increasing network speeds of today's Internet require high-performance, high-throughput network devices. However, the lack of affordable, flexible, and readily available devices poses a challenge for packet classification and filtering. This problem is exacerbated by the increase in volumetric Distributed Denial-of-Service (DDoS) attacks, which require efficient packet processing and filtering. To meet the demands of high-speed networks and configurable network processing devices, this paper investigates a hybrid hardware/software packet filter prototype that combines reconfigurable FPGA technology and high-speed software filtering on commodity hardware. It uses a novel approach that offloads filtering rules to the hardware and employs a Longest Prefix Matching (LPM) algorithm and allowlists/blocklists based on millions of IP prefixes. The hybrid filter demonstrates improvements over software-only filtering, achieving performance gains of nearly 30%, depending on the rulesets, offloading methods, and traffic types. The significance of this research lies in developing a cost-effective alternative to more-expensive or less-effective filters, providing high-speed DDoS packet filtering for IPv4 traffic, as it still dominates over IPv6. Deploying these filters on commodity hardware at the edge of the network can mitigate the impact of DDoS attacks on protected networks, enhancing the security of all devices on the network, including Internet of Things (IoT) devices.

摘要

当今互联网不断提高的网络速度需要高性能、高吞吐量的网络设备。然而,缺乏价格合理、灵活且易于获得的设备给数据包分类和过滤带来了挑战。随着大容量分布式拒绝服务(DDoS)攻击的增加,这个问题变得更加严重,因为DDoS攻击需要高效的数据包处理和过滤。为了满足高速网络和可配置网络处理设备的需求,本文研究了一种混合硬件/软件数据包过滤器原型,该原型将可重构FPGA技术与商品硬件上的高速软件过滤相结合。它采用了一种新颖的方法,将过滤规则卸载到硬件上,并采用最长前缀匹配(LPM)算法以及基于数百万个IP前缀的允许列表/阻止列表。根据规则集、卸载方法和流量类型,混合过滤器相对于仅软件过滤有了改进,性能提升近30%。这项研究的意义在于开发一种比更昂贵或效率更低的过滤器更具成本效益的替代方案,为IPv4流量提供高速DDoS数据包过滤,因为IPv4仍比IPv6占主导地位。在网络边缘的商品硬件上部署这些过滤器可以减轻DDoS攻击对受保护网络的影响,增强网络上所有设备(包括物联网(IoT)设备)的安全性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/64b3547f59f9/sensors-23-07636-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/87fdc21690d5/sensors-23-07636-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/7151d9b1db42/sensors-23-07636-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/748e8bc80dcd/sensors-23-07636-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/f00adfd5b380/sensors-23-07636-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/da24d4f46422/sensors-23-07636-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/0d4304d4dc77/sensors-23-07636-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/49e8fc75802d/sensors-23-07636-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/d020b7db3de4/sensors-23-07636-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/b0a7a6716b84/sensors-23-07636-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/64b3547f59f9/sensors-23-07636-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/87fdc21690d5/sensors-23-07636-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/7151d9b1db42/sensors-23-07636-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/748e8bc80dcd/sensors-23-07636-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/f00adfd5b380/sensors-23-07636-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/da24d4f46422/sensors-23-07636-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/0d4304d4dc77/sensors-23-07636-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/49e8fc75802d/sensors-23-07636-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/d020b7db3de4/sensors-23-07636-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/b0a7a6716b84/sensors-23-07636-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1814/10490799/64b3547f59f9/sensors-23-07636-g010.jpg

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本文引用的文献

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Review of State-of-the-Art FPGA Applications in IoT Networks.物联网网络中前沿现场可编程门阵列应用综述。
Sensors (Basel). 2022 Oct 2;22(19):7496. doi: 10.3390/s22197496.