A New Wavelet Thresholding Method Based On Cyclostationarity For Enhancing The Interception Of Computer Video Leakage Signals

Computer displays emit electromagnetic waves, which leak the information displayed by the computers. Electromagnetic radiation signals from computer displays can be a security risk if they are intercepted and reconstructed. Signal to noise ratios (SNR) of video leakage signal are usually low due to the environmental noise and many other man-made noises. This can seriously influence the quality of the reconstructed image and further processing of video leakage signals. In this paper, a new cyclostationarity wavelet thresholding method is proposed for enhancing the interception of the video leakage signals by improving the SNR of signals. We analyzed the cyclostationarity property of computer video leakage signals, and then we used that property to improve the performance of wavelet thresholding method and the performance of preprocessing computer video leakage signals. We pre-processed one-dimensional leakage signals without reconstructing the image in order to process signals more efficiently. At the same time, the performance of processing image can also be improved as long as the processed signal can be reconstructed to an image. The processed results of the actual experimental data show that the proposed algorithm performs better both on denoising one-dimensional signal and two-dimensinal reconstructed image than the other four wavelet thresholding methods which are Square-Root-Log, Minimax principle, Heursure and Rigrsure.