Date of Award:
Master of Science (MS)
Electrical and Computer Engineering
In recent years, the researchers and engineers have realized that the trustiness of computer and networking devices and hardware can no longer be examined properly using the existing identification and security checking methods that operate based on the digital representation of data. As an example, since the digital identifiers can be copied, it is difficult to tie a digital identity to a device for sure. Also, the new or present created cyber attacks can manipulate the used digital data in a network easily. Due to these issues, the trend in development of new identification and security checking methods has moved toward analog signals of the devices that can be acquired from different parts of their circuits. In fact, these analog signals have adequate information and features to uniquely identify the devices.
The dark side of analog-based methods is when some changes appear in the behavior of devices in different conditions and over time. It causes the loss of ability of these methods in differentiation of the devices. This is due to the mismatch between the current signal of the device and the reference signal, which is obtained earlier. In this regard, a number of statistical models are designed that use the environmental or a device’s circuit-related parameters in order to predict its future behavior. The achieved results from running the designed statistical models on the related data show that the surrounding temperature of the device is the best option for predicting its signal information and features.
In the last part of this study, the defending strength of an analog-based identification and security checking method in confrontation with a specific attack is evaluated. In the utilized attack, the forged version of a device’s signal is generated and is checked by the security method. According to the outcomes of accomplished experiments, the leveraged security checking method is able to defeat this attack perfectly.
Taheri, Shayan, "Evaluation of Tracking Regimes for, and Security of, PLI Systems" (2015). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 4549.
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