首页> 外文期刊>IEEE transactions on network and service management >Towards Effective Trust-Based Packet Filtering in Collaborative Network Environments
【24h】

Towards Effective Trust-Based Packet Filtering in Collaborative Network Environments

机译:在协作网络环境中实现有效的基于信任的数据包筛选

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

Overhead network packets are a big challenge for intrusion detection systems (IDSs), which may increase system burden, degrade system performance, and even cause the whole system collapse, when the number of incoming packets exceeds the maximum handling capability. To address this issue, packet filtration is considered as a promising solution, and our previous research efforts have proven that designing a trust-based packet filter was able to refine unwanted network packets and reduce the workload of a local IDS. With the development of Internet cooperation, collaborative intrusion detection environments (e.g., CIDNs) have been developed, which allow IDS nodes to collect information and learn experience from others. However, it would not be effective for the previously built trust-based packet filter to work in such a collaborative environment, since the process of trust computation can be easily compromised by insider attacks. In this paper, we adopt the existing CIDN framework and aim to apply a collaborative trust-based approach to reduce unwanted packets. More specifically, we develop a collaborative trust-based packet filter, which can be deployed in collaborative networks and be robust against typical insider attacks (e.g., betrayal attacks). Experimental results in various simulated and practical environments demonstrate that our filter can perform effectively in reducing unwanted traffic and can defend against insider attacks through identifying malicious nodes in a quick manner, as compared to similar approaches.
机译:开销网络数据包是入侵检测系统(IDS)的一大挑战,当传入数据包的数量超过最大处理能力时,IDS可能会增加系统负担,降低系统性能,甚至导致整个系统崩溃。为了解决此问题,数据包过滤被认为是一种有前途的解决方案,并且我们之前的研究工作已经证明,设计基于信任的数据包过滤器能够优化不需要的网络数据包并减少本地IDS的工作量。随着互联网合作的发展,已经开发了协作入侵检测环境(例如,CIDN),其允许IDS节点收集信息并从其他节点学习经验。但是,以前建立的基于信任的数据包筛选器无法在这种协作环境中工作,因为信任计算很容易受到内部攻击者的破坏。在本文中,我们采用现有的CIDN框架,旨在采用基于协作信任的方法来减少不需要的数据包。更具体地说,我们开发了基于协作的基于信任的数据包筛选器,可将其部署在协作网络中,并且能够抵抗典型的内部攻击(例如,背叛攻击)。在各种模拟和实际环境中的实验结果表明,与类似方法相比,我们的过滤器可以有效地减少不必要的流量,并且可以通过快速识别恶意节点来防御内部攻击。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号