A Metaheuristic Approach to Secure Multimedia Big Data for IoT-Based Smart City Applications

Abstract

Media streaming falls into the category of Big Data. Regardless of the video duration, an enormous amount of information is encoded in accordance with standardized algorithms of videos. In the transmission of videos, the intended recipient is allowed to receive a copy of the broadcasted video; however, the adversary also has access to it which poses a serious concern to the data confidentiality and availability. In this paper, a cryptographic algorithm, Advanced Encryption Standard, is used to conceal the information from malicious intruders. However, in order to utilize fewer system resources, video information is compressed before its encryption. Various compression algorithms such as Discrete Cosine Transform, Integer Wavelet transforms, and Huffman coding are employed to reduce the enormous size of videos. moving picture expert group is a standard employed in video broadcasting, and it constitutes of different frame types, viz., I, B, and P frames. Later, two frame types carry similar information as of foremost type. Even I frame is to be processed and compressed with the abovementioned schemes to discard any redundant information from it. However, I frame embraces an abundance of new information; thus, encryption of this frame is sufficient enough to safeguard the whole video. The introduction of various compression algorithms can further increase the encryption time of one frame. The performance parameters such as PSNR and compression ratio are examined to further analyze the proposed model’s effectiveness. Therefore, the presented approach has superiority over the other schemes when the speed of encryption and processing of data are taken into consideration. After the reversal of the complete system, we have observed no major impact on the quality of the deciphered video. Simulation results ensure that the presented architecture is an efficient method for enciphering the video information.