With the advancement of technology, Unmanned Aerial Vehicles (UAVs), also known as drones, are being used in numerous applications. However, the illegal use of UAVs, such as in terrorism and spycams, has also increased, which has led to active research on anti-drone methods. Various anti-drone methods have been proposed over time; however, the most representative method is to apply intentional electromagnetic interference to drones, especially to their sensor modules. In this paper, we review various studies on the effect of intentional electromagnetic interference (IEMI) on the sensor modules. Various studies on IEMI sources are reviewed and classified on the basis of the power level, information needed, and frequency. To demonstrate the application of drone-sensor modules, major sensor modules used in drones are briefly introduced, and the setup and results of the IEMI experiment performed on them are described. Finally, we discuss the effectiveness and limitations of the proposed methods and present perspectives for further research necessary for the actual application of anti-drone technology.

This paper proposes a method to reconstruct an original video display from electromagnetic leakage by using the characteristics of digital video interfaces (e.g., digital visual interface (DVI) and high-definition multimedia interface (HDMI)). Moreover, it is proven that the analysis is applicable through a very narrow multiband pass filter when multiple video display units (VDUs) with identical video properties (resolution, refresh rate, etc.) are placed together and emanate simultaneously. The proposed method is verified with our reconstruction system and is expected to contribute to improving the security of video display signals by raising awareness regarding information leakage risks.

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This paper investigates the electromagnetic interference characteristics of the transitionminimized differential signaling (TMDS) scheme, a well-known technology for rapid serial data transmission, from a radio communication perspective. Such scrutiny regarding the leaking phenomenon inspires a pseudo model of the compromising signal model, which can simultaneously consider behavioral features of the software-defined radio with a simple RF front-end measuring the leakage. In this work, a conceptual explanation with mathematical formulations in implementing the pseudo model has been presented. Subsequently, by merging the model with various extra noises being in nature, the model can be utilized to facilitate and quantify the possibility of information extraction from the defected electromagnetic signatures. Furthermore, it is interesting to note that there are asynchronous problems due to inevitable timing errors in video display devices, even with a sophisticated acquisition system, turning out to be fatal for the frame-averaging scheme conducted before the signal demodulation. In view of these challenges, we have formulated a synchronizing scheme and verified validity by utilizing the pseudo model with the extra noise to take into account the asynchronous problem. Moreover, the structural similarity (SSIM), a function of the signal-to-noise ratio, can provide the number of frames for the frame-averaging process and eventually give the minimum acquisition time to earn meaningful information from the compromising emanation. Finally, after the appropriate post-processing, the extracted information from the actual measurements is compared with the reconstruction from the pseudo-model results revealing excellent agreements.

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