Firewall engine based on Graphics Processing Unit

A. Sahoo, Amardeep Das, Mayank Tiwary
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引用次数: 7

Abstract

Firewalls are very important elements in network security. Working of firewall rules for enterprise network has become complex, error-prone and time-consuming. Firewall filtering rules have to be carefully written and organized in order to correctly implement the security policy. The main issue is the slow filtering action during heavy load. To reduce the time consumption there is a very urgent need of optimized firewall engine, which runs on GPU's. We mainly focus on the creating parallel algorithms for desktop firewall which reduces the time consumption and at the same time it can allow for strong threat detection, intrusion detection of incoming packets. In our paper we have created parallel optimized algorithms for intrusion detection, threat detection, packet filtering and network address translation which runs on NVIDIA's GPU card and it is based on CUDA programming. For our experimental analysis, we have created test packets and for virus scanning we have used the virus-signatures from Clam-AV.
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防火墙引擎基于图形处理单元
防火墙是网络安全的重要组成部分。企业网络防火墙规则的工作变得复杂、容易出错和耗时。为了正确实现安全策略,必须仔细编写和组织防火墙过滤规则。主要问题是在高负载时过滤速度慢。为了减少时间消耗,迫切需要优化运行在GPU上的防火墙引擎。本文主要研究了桌面防火墙并行算法的创建,在减少时间消耗的同时,可以对传入的数据包进行强威胁检测、入侵检测。在本文中,我们基于CUDA编程,在NVIDIA的GPU卡上创建了入侵检测、威胁检测、包过滤和网络地址转换的并行优化算法。为了进行实验分析,我们创建了测试包,并使用了来自Clam-AV的病毒签名进行病毒扫描。
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