A HEVC Video Steganalysis Method Using the Optimality of Motion Vector Prediction

作     者：Jun Li Minqing Zhang Ke Niu Yingnan Zhang Xiaoyuan Yang 

作者机构：College of Cryptography EngineeringEngineering University of the Chinese People’s Armed Police ForceXi’an710086China Key Laboratory of Network and Information Security of the Chinese People’s Armed Police ForceXi’an710086China 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2024年第79卷第5期

页      面：2085-2103页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：the National Natural Science Foundation of China(Grant Nos.62272478 62202496 61872384). 

主　　题：Video steganography video steganalysis motion vector prediction motion vector difference advanced motion vector prediction local optimality 

摘      要：Among steganalysis techniques,detection against MV(motion vector)domain-based video steganography in the HEVC(High Efficiency Video Coding)standard remains a challenging issue.For the purpose of improving the detection performance,this paper proposes a steganalysis method that can perfectly detectMV-based steganography in HEVC.Firstly,we define the local optimality of MVP(Motion Vector Prediction)based on the technology of AMVP(Advanced Motion Vector Prediction).Secondly,we analyze that in HEVC video,message embedding either usingMVP index orMVD(Motion Vector Difference)may destroy the above optimality of MVP.And then,we define the optimal rate of MVP as a steganalysis feature.Finally,we conduct steganalysis detection experiments on two general datasets for three popular steganographymethods and compare the performance with four state-ofthe-art steganalysis methods.The experimental results demonstrate the effectiveness of the proposed feature set.Furthermore,our method stands out for its practical applicability,requiring no model training and exhibiting low computational complexity,making it a viable solution for real-world scenarios.