Fake Bitrate Detection of HEVC Videos Based on Prediction Process

• Published in: Symmetry (Basel) Vol. 11; no. 7; p. 918
• Main Authors: Liang, Xiaoyun, Li, Zhaohong, Li, Zhonghao, Zhang, Zhenzhen
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2019
• Subjects: Algorithms; Classification; Coding; Coding standards; Feature extraction; Methods; Partitioning; Support vector machines; Video compression
• ISSN: 2073-8994; 2073-8994
• DOI: 10.3390/sym11070918

In order to defraud click-through rate, some merchants recompress the low-bitrate video to a high-bitrate one without improving the video quality. This behavior deceives viewers and wastes network resources. Therefore, a stable algorithm that detects fake bitrate videos is urgently needed. High-Efficiency Video Coding (HEVC) is a worldwide popular video coding standard. Hence, in this paper, a robust algorithm is proposed to detect HEVC fake bitrate videos. Firstly, five effective feature sets are extracted from the prediction process of HEVC, including Coding Unit of I-picture/P-picture partitioning modes, Prediction Unit of I-picture/P-picture partitioning modes, Intra Prediction Modes of I-picture. Secondly, feature concatenation is adopted to enhance the expressiveness and improve the effectiveness of the features. Finally, five single feature sets and three concatenate feature sets are separately sent to the support vector machine for modeling and testing. The performance of the proposed algorithm is compared with state-of-the-art algorithms on HEVC videos of various resolutions and fake bitrates. The results show that the proposed algorithm can not only can better detect HEVC fake bitrate videos, but also has strong robustness against frame deletion, copy-paste, and shifted Group of Picture structure attacks.