Jeonghwan Heo

Bio: Jeonghwan Heo is an academic researcher from Hanyang University. The author has contributed to research in topics: Encryption & Codec. The author has co-authored 1 publications.

Deceptive Techniques to Hide a Compressed Video Stream for Information Security.

Abstract: With the recent development of video compression methods, video transmission on traditional devices and video distribution using networks has increased in various devices such as drones, IP cameras, and small IoT devices. As a result, the demand for encryption techniques such as MPEG-DASH for transmitting streams over networks is increasing. These video stream security methods guarantee stream confidentiality. However, they do not hide the fact that the encrypted stream is being transmitted over the network. Considering that sniffing attacks can analyze the entropy of the stream and scan huge amounts of traffic on the network, to solve this problem, the deception method is required, which appears unencrypted but a confidential stream. In this paper, we propose the new deception method that utilizes standard NAL unit rules of video codec, where the unpromised device shows the cover video and the promised device shows the secret video for deceptive security. This method allows a low encryption cost and the stream to dodge entropy-based sniffing scan attacks. The proposed stream shows that successful decoding using five standard decoders and processing performance was 61% faster than the conventional encryption method in the test signal conformance set. In addition, a network encrypted stream scan method the HEDGE showed classification results that our stream is similar to a compressed video.

Video Steganography in IoT: Information Embedding using OpenCV and 2LSB

Abstract: After a review of many research study it is been concluded that various security techniques are used for data transmission in Internet of Things (IoT) devices. Considerable progress has been made in enhancing data transmission security, but still, some gaps exist. Existing steganography techniques exhibit gaps such as limited concealing capacity, substandard quality of stego files, and reduced resilience when faced with image processing attacks. To overcome some of the existing gaps proposed work utilizes video steganography. In this work, a video steganography technique for securing data transmission in IoT devices has been proposed using OpenCV and Least Significant Bit (LSB). Extraction of video frames for hiding secret data has been done using OpenCV and then concealing the secret message is employed by the 2 LSB technique. The two Least Significant Bits are modified to hide the secret message. OpenCV facilitates the identification of suitable regions of interest for concealing secret data, leading to enhanced robustness in hiding information. Videos offer a wide range of possibilities for embedding secret information, resulting in a significant capacity for concealment and imperceptibility. For measuring the performance of research work Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Entropy, and Histogram analysis are done.