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A Novel Method for Malicious Implanted Computer Video Cable Detection via Electromagnetic Features

机译:通过电磁特征进行恶意植入计算机视频电缆检测的新方法

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Electromagnetic (EM) radiation is an inherent phenomenon in the operation of electronic information equipment. The side-channel attack, malicious hardware and software implantation attack by using the EM radiation are implemented to steal information. This form of attacks can be used in air-gap information equipment, which bring great danger for information security. The malicious implantation hidden in circuits are difficult to detect. How to detect the implantation is a challenging problem. In this paper, a malicious hardware implantation is analyzed. A method that leverages EM signals for Trojan-embedded computer video cable detection is proposed. The method neither needs activating the Trojan nor requires near-field probe approaching at close. It utilizes recognizable patterns in the spectrum of EM to predict potential risks. This paper focuses on the extraction of feature vectors via the empirical mode decomposition (EMD) algorithm. Intrinsic mode functions (IMFs) are analyzed and selected to be eigenvectors. Using a common classification technique, we can achieve both effective and reliable detection results.
机译:电磁(EM)辐射是电子信息设备操作中的固有现象。通过使用EM辐射的侧通道攻击,恶意硬件和软件植入攻击以窃取信息。这种形式的攻击可以用于气隙信息设备,这带来了极大的信息安全危险。隐藏在电路中的恶意植入难以检测。如何检测植入是一个具有挑战性的问题。本文分析了恶意硬件植入。提出了一种利用EM信号进行特洛伊木马嵌入式计算机视频电缆检测的方法。该方法既不需要激活木马,也不需要在关闭附近接近近场探测。它利用EM频谱中的可识别模式来预测潜在的风险。本文通过经验模式分解(EMD)算法,专注于特征向量的提取。分析内在模式功能(IMF)并选择为特征向量。使用常见的分类技术,我们可以实现有效且可靠的检测结果。

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