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Cognitive Radio Based System for Best Effort Communications in Sound-based Covert Channel for IoT Environments

机译:基于认知无线电的系统,以获得基于声音的秘密信道的最佳努力通信

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Nowadays, the use of nodes with different sensing capabilities is pervasive. This leads to many environments capable of monitoring human activity for security, comfort, and connectivity applications among others. However, this also leads to many opportunities for security breaches in personal mobile devices when they are in such environments. In this work, we focus on a covert channel communication system based on sound waves with cognitive radio capabilities. In such system, the mobile nodes are infected with malware that allows the attacker to obtain information from the devices, sending data using a covert channel (hidden communications) to neighbor sensor nodes used for IoT applications through sound waves imperceptible to human ears. A cognitive radio design is based on allowing such hidden communications to occur when the primary channel is unused (i.e., when the user is not using or handling its device). As such, the primary network is considered to be any activity of the mobile (communication, application or service) and the secondary network is the covert channel communication system. Such a system is studied and mathematically analyzed using Continuous Time Markov Chains in order to obtain the throughput in the covert channel for different system parameters. A main result from this work is that, a careful selection of the activation parameter can lead to a more efficient covert data transfer system, irrespective of the rest of the system parameters.
机译:如今,使用具有不同传感功能的节点是普遍存在的。这导致许多能够监控人类活动的安全性,舒适和连接应用等。然而,当他们在这样的环境中,这也会导致个人移动设备中的安全漏洞的许多机会。在这项工作中,我们专注于基于具有认知无线电能力的声波的隐蔽信道通信系统。在这种系统中,移动节点被恶意软件感染,允许攻击者从设备获取信息,使用封面信道(隐藏通信)向邻居传感器节点通过人类耳朵无法察觉的声波来获取用于IOT应用的邻居传感器节点。认知无线电设计是基于允许当主信道未使用时发生这种隐藏通信(即,当用户未使用或处理其设备时)。这样,主网络被认为是移动(通信,应用程序或服务)的任何活动,并且辅助网络是封面信道通信系统。使用连续时间Markov链进行研究和数学地分析这样的系统,以便获得不同系统参数的封面通道中的吞吐量。这项工作的主要结果是,仔细选择激活参数可以导致更有效的隐蔽数据传输系统,而不管系统参数的其余部分如何。

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