| IPv6网络攻击事件溯源中的攻击树节点特征定位 |
投稿时间：2023-03-24 修订日期：2023-04-03  点此下载全文 |
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| 基金项目:福建华电可门发电有限公司发电企业生产控制网络安全综合防护与智能管理平台研究与应用项目,项目名称：基于特征梯度的网络周期拒绝服务攻击识别研究，项目编号：BU-01-2203010 福建省科技计划重大项目(2013H6015) |
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| 中文摘要:在网络普及的现代，各类网络协议层出不穷，而在当下最为普遍的便是Ipv6网络协议，其虽然优化解决了前网络协议中存在的部分问题，但是依旧存在各类安全隐患，为了能更好的预防并构建网络防御系统，需要对过往攻击事件中的攻击树节点特征实施提取，为此提出IPv6网络攻击事件溯源中的攻击树节点特征定位。该方法首先利用攻击类型实施扩展，得到攻击树模型，并以此展开计算，之后结合深度学习网络对攻击树的节点特征实施提取，最后利用DV-Hop方法对提取到的攻击树节点特征实施定位。所提方法在定位过程中不仅能耗低，而且误差小，不易受环境干扰，定位稳定性较好，定位效率较高，可以更有效的为改进网络防御系统提供数据支持。 |
| 中文关键词:IPv6网络 攻击树 节点特征 特征定位 事件溯源 |
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| Attack tree node feature location in IPv6 network attack event source tracing |
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| Abstract:In the modern era of network popularization, various network protocols emerge one after another. At present, the most common is the Ipv6 network protocol. Although it has optimized and solved some problems in the previous network protocols, there are still various security risks. In order to better prevent and build a network defense system, it is necessary to extract the characteristics of attack tree nodes in past attacks, Therefore, the node feature location of attack tree in IPv6 network attack event traceability is proposed. This method first uses the attack type to expand and obtain the attack tree model, and then calculates based on this model. Then it combines the deep learning network to extract the node features of the attack tree, and finally uses the DV Hop method to locate the extracted node features of the attack tree. The proposed method not only has low energy consumption, but also has small error and good positioning performance, which can provide more effective data support for improving the network defense system. |
| keywords:IPv6 network attack tree node features feature location event source tracing |
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