基于联盟区块链的网络攻击签名和特征分发架构

O. Ajayi, O. Igbe, T. Saadawi
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引用次数: 8

摘要

入侵检测系统(IDS)是检测计算机网络中恶意流量的有效方法之一。虽然IDS可以识别网络中的恶意活动,但可能很难检测到分布式或协同攻击,因为它们只有一个有利位置。针对这一问题,提出了协同入侵检测系统。在此检测系统中,节点交换攻击特征或签名,以检测系统中其他节点先前检测到的攻击。交换攻击特征是必要的,因为在不同位置经历的零日攻击(没有已知签名的攻击)是不一样的。尽管该解决方案增强了单个IDS响应以前由协作节点识别的攻击的能力,但恶意活动(如虚假数据注入、数据操作或删除以及数据一致性)是威胁该方法的问题。在本文中,我们提出了一种利用区块链的分布式技术、防篡改能力和数据不变性来检测和防止恶意活动,解决协同入侵检测面临的数据一致性问题的解决方案。专注于协同入侵检测的提取、存储和分发阶段,我们开发了一种基于区块链的解决方案,可以安全地提取特征或签名,增加额外的验证步骤,使这些签名和特征的存储分布式和数据共享安全。从响应时间和抵抗特征/签名注入两方面对系统进行了性能评估。结果表明,该解决方案可以防止存储攻击特征或签名,防止恶意数据注入、操纵或删除,并且具有低延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Consortium Blockchain-Based Architecture for Cyber-attack Signatures and Features Distribution
One of the effective ways of detecting malicious traffic in computer networks is intrusion detection systems (IDS). Though IDS identify malicious activities in a network, it might be difficult to detect distributed or coordinated attacks because they only have single vantage point. To combat this problem, cooperative intrusion detection system was proposed. In this detection system, nodes exchange attack features or signatures with a view of detecting an attack that has previously been detected by one of the other nodes in the system. Exchanging of attack features is necessary because a zero-day attacks (attacks without known signature) experienced in different locations are not the same. Although this solution enhanced the ability of a single IDS to respond to attacks that have been previously identified by cooperating nodes, malicious activities such as fake data injection, data manipulation or deletion and data consistency are problems threatening this approach. In this paper, we propose a solution that leverages blockchain's distributive technology, tamper-proof ability and data immutability to detect and prevent malicious activities and solve data consistency problems facing cooperative intrusion detection. Focusing on extraction, storage and distribution stages of cooperative intrusion detection, we develop a blockchain-based solution that securely extracts features or signatures, adds extra verification step, makes storage of these signatures and features distributive and data sharing secured. Performance evaluation of the system with respect to its response time and resistance to the features/signatures injection is presented. The result shows that the proposed solution prevents stored attack features or signature against malicious data injection, manipulation or deletion and has low latency.
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