加权攻击图中攻击轨迹最短的物联网系统漏洞分析与网络加固

Yinxin Wan, Xuanli Lin, Abdulhakim Sabur, A. Chang, Kuai Xu, G. Xue
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引用次数: 0

摘要

近年来,物联网(IoT)设备已广泛部署在边缘网络中,包括智能家居和办公室。尽管物联网的进步提供了令人兴奋的机会,但它也在系统中引入了新的攻击媒介和漏洞。已有研究表明,攻击图是进行物联网安全系统级分析的有效模型。本文主要研究物联网系统的漏洞分析和网络加固。首先将攻击图的概念扩展到加权攻击图,设计了一种计算加权攻击图中最短攻击轨迹的新算法。然后,我们提出了网络硬化问题。我们证明了这个问题是np困难的,然后设计了一个精确算法和一个启发式算法来解决它。在9个合成物联网系统和2个真实智能家居物联网测试平台上进行的大量实验表明,我们的最短攻击跟踪算法鲁棒且快速,与精确算法相比,我们的启发式网络强化算法在产生接近最佳结果方面效率高。
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IoT System Vulnerability Analysis and Network Hardening with Shortest Attack Trace in a Weighted Attack Graph
In recent years, Internet of Things (IoT) devices have been extensively deployed in edge networks, including smart homes and offices. Despite the exciting opportunities afforded by the advancements in the IoT, it also introduces new attack vectors and vulnerabilities in the system. Existing studies have shown that the attack graph is an effective model for performing system-level analysis of IoT security. In this paper, we study IoT system vulnerability analysis and network hardening. We first extend the concept of attack graph to weighted attack graph and design a novel algorithm for computing a shortest attack trace in a weighted attack graph. We then formulate the network hardening problem. We prove that this problem is NP-hard, and then design an exact algorithm and a heuristic algorithm to solve it. Extensive experiments on 9 synthetic IoT systems and 2 real-world smart home IoT testbeds demonstrate that our shortest attack trace algorithm is robust and fast, and our heuristic network hardening algorithm is efficient in producing near optimal results compared to the exact algorithm.
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