<p dir="ltr">Unintentional electromagnetic emission (called emanation) from electronic devices and cables contains a significant correlation with the source signal and can be used to recover otherwise confidential data. In our work, EM emanation has been exploited to recover keystrokes from USB keyboards. Also, such emission has been utilized to form a covert channel for data exfiltration from air-gapped devices without being detected by IDS. To protect sensitive information, an automated emanation detection system has been proposed by developing two emanation detection algorithms (CNN-based and harmonic-based) through the characterization of emanation signals from a wide range of devices. Apart from emanation, data theft can happen due to the failure of access control methods. Traditional wireless devices are susceptible to various spoofing attacks as they only use digital signature-based authentication systems, ignoring the physical signatures completely. To circumvent that, RF-PUF was proposed to use device-specific signatures to be used for trust augmentation in traditional methods. By forming an extensive experimental dataset, we established RF-PUF as a strong PUF with a low-power overhead that outperformed the state-of-the-art methods and is robust against typical attacks. For real-time authentication, we proposed DIRAC, which forms dynamic device clusters and incrementally learns as more device data becomes available. Since our root of trust is in the physical signature of the ICs, they also need to be secured. However, counterfeited ICs may jeopardize that goal. We have proposed RF-PSF, which uses device-specific physical properties to authenticate its process technology which is a big part of the cloned IC detection.</p>