Third Eye: Context-Aware Detection for Hidden Terminal Emulation Attacks in Cognitive Radio-Enabled IoT Networks
Third Eye: Context-Aware Detection for Hidden Terminal Emulation Attacks in Cognitive Radio-Enabled IoT Networks
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DOI：
10.1109/tccn.2020.2968324
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发表时间：
2020-01
影响因子：
8.6
通讯作者：
Moinul Hossain;Jiang Xie
中科院分区：
文献类型：
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作者：
Moinul Hossain;Jiang Xie
最近，物联网（IoT）技术已经引起越来越多的关注，因为它在广泛的应用中具有积极影响人类生活的巨大潜力。尽管如此，可能遵循不同无线协议的多个共址物联网网络的密集部署将本质上带来新的网络漏洞。在本文中，我们介绍了一种新的攻击场景在协同定位的认知无线电（CR）启用物联网网络，其中反应式攻击者可以模拟隐藏终端的辐射模式（攻击者来自不同的网络），并可以干扰其隐藏的对手，即隐藏终端仿真（HTE）攻击的传输。由于来自不同网络和技术的物联网节点的密集部署将自然地在不同网络的物联网设备之间创建这种隐藏终端场景，因此它为HTE攻击者提供了合理的可否认性，以反应性地干扰其隐藏的对应方;因此，在良性隐藏终端可能被标记为反应性攻击者的这种场景中，最先进的反应性攻击检测技术是不可行的。在本文中，我们捕获的行为，一个良性的隐藏终端和HTE攻击者通过简约马尔可夫模型，并提出了一个上下文感知的检测解决方案，使用马尔可夫链假设检验，即第三只眼。虽然恶意干扰检测已经有了广泛的研究，但据我们所知，这项工作是第一个将隐藏终端视为良性干扰源，预见到这种独特的攻击场景，并利用现有的载波侦听技术作为检测HTE攻击的自然有效方法。
Recently, the Internet of Things (IoT) technology has been drawing increasing attention because it has a great potential to positively impact human life in a broad range of applications. Nonetheless, the dense deployment of multiple co-located IoT networks that may follow different wireless protocols will essentially bring new network vulnerabilities. In this paper, we introduce a novel attack scenario in co-located cognitive radio (CR) enabled IoT networks, where a reactive attacker can emulate the radiation pattern of a hidden terminal (the attacker is from a different network) and can interfere with the transmissions from its hidden counterparts, namely the hidden terminal emulation (HTE) attack. As the dense deployment of IoT nodes—from different networks and technologies—will naturally create such hidden terminal scenarios among IoT devices of different networks, it provides the HTE attacker plausible deniability to reactively interfere with its hidden counterparts; hence, the state-of-the-art reactive attack detection techniques are infeasible in this scenario where benign hidden terminals could be flagged as reactive attackers. In this paper, we capture the behavior of a benign hidden terminal and an HTE attacker via parsimonious Markov models and propose a context-aware detection solution using the Markov chain hypothesis testing, namely the Third Eye. Though there has been extensive research on malicious interference detection, to the best of our knowledge, this work is the first that considers hidden terminals as benign interference sources, foresees this unique attack scenario, and leverages the existing carrier sensing technique as a natural and effective way to detect HTE attacks.