网络拓扑混淆:挑战、解决方案和比较

IF 30.4 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Changhao Qiu, Bangbang Ren, Lailong Luo, Deke Guo
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引用次数: 0

摘要

攻击者通过推断网络拓扑结构来定位关键组件,并规划高成功率的经济有效的攻击。网络拓扑混淆(NTO)通过暴露一个设计良好的假拓扑来解决这个问题,这个假拓扑会误导推理并提高攻击成本。现有的调查涵盖了拓扑推理,但对主动防御的关注有限。我们将NTO机制分解为三个工作流程阶段,即识别、生成和部署,并将其分解为四种基本技术,即重路由、虚拟网络、响应制造和数据包干预,它们的组合构成了每一种工作流程。然后从技术和设计目标两方面系统分析了多种NTO机制,并概述了未来的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Network Topology Obfuscation: Challenges, Solutions, and Comparisons
Attackers infer the network topology to locate critical components and to plan cost-effective attacks with high success rates. Network topology obfuscation (NTO) counters this by exposing a well-designed fake topology that misleads the inference and raises the cost of attack. Existing surveys cover topology inference but give limited attention to proactive defense. We disassemble the NTO mechanisms into three workflow phases, identification, generation and deployment, and into four fundamental techniques, rerouting, virtual network, response fabricating and packet intervention, whose combination forms each of them. We then systematically analyze multiple NTO mechanisms by technique and design objective, and outline future research directions.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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