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 detectio...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.展开更多
A novel fast sub-pixel search algorithm is proposed to accelerate sub-pixel search. Based on the features of predicted motion vector (PMV) and texture direction observed, the proposed method effectively filters out im...A novel fast sub-pixel search algorithm is proposed to accelerate sub-pixel search. Based on the features of predicted motion vector (PMV) and texture direction observed, the proposed method effectively filters out impossible points and thus decreases 11 searched points in average during the sub-pixel search stage. A threshold is also adopted to early terminate the sub-pixel search. Simulation results show that the proposed method can achieve up to 4.8 times faster than full sub-pixel motion search scheme (FSPS) with less than 0.025 dB PSNR losses and 2.2% bit-length increases.展开更多
Recently proposed steganalysis methods based on the local optimality of motion vector prediction(MVP)indicate that the existing HEVC(high efficiency video coding)motion vector(MV)domain video steganography algorithms ...Recently proposed steganalysis methods based on the local optimality of motion vector prediction(MVP)indicate that the existing HEVC(high efficiency video coding)motion vector(MV)domain video steganography algorithms can disturb the optimality of MVP in advanced motion vector prediction(AMVP)technology.In order to improve the security of steganography algorithm,this paper proposes an MV domain steganography method in HEVC based on MVP’s index and motion vector difference(MVD).First,we analyze the conditions that need to be met for steganography to resist attacks from MVP’s optimality features and other traditional steganalysis features.Then,a distortion function for minimizing embedding distortion is designed,and an algorithm for secret message embedding and extraction in units of inter-frame is proposed.Experimental results show that the proposed algorithm can resist attacks based on the optimality of MVP and also has high security against other traditional steganalysis methods.In addition,the proposed algorithm has excellent performance in visual quality and coding efficiency,and can be applied to practical scenarios of video covert communication.展开更多
基金the National Natural Science Foundation of China(Grant Nos.62272478,62202496,61872384).
文摘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.
基金Supported by Electronic Information Industry Foundation of China (No.[2005]635) .
文摘A novel fast sub-pixel search algorithm is proposed to accelerate sub-pixel search. Based on the features of predicted motion vector (PMV) and texture direction observed, the proposed method effectively filters out impossible points and thus decreases 11 searched points in average during the sub-pixel search stage. A threshold is also adopted to early terminate the sub-pixel search. Simulation results show that the proposed method can achieve up to 4.8 times faster than full sub-pixel motion search scheme (FSPS) with less than 0.025 dB PSNR losses and 2.2% bit-length increases.
基金supported by the National Natural Science Foundation of China(Nos.62102450,62272478,and 62202496).
文摘Recently proposed steganalysis methods based on the local optimality of motion vector prediction(MVP)indicate that the existing HEVC(high efficiency video coding)motion vector(MV)domain video steganography algorithms can disturb the optimality of MVP in advanced motion vector prediction(AMVP)technology.In order to improve the security of steganography algorithm,this paper proposes an MV domain steganography method in HEVC based on MVP’s index and motion vector difference(MVD).First,we analyze the conditions that need to be met for steganography to resist attacks from MVP’s optimality features and other traditional steganalysis features.Then,a distortion function for minimizing embedding distortion is designed,and an algorithm for secret message embedding and extraction in units of inter-frame is proposed.Experimental results show that the proposed algorithm can resist attacks based on the optimality of MVP and also has high security against other traditional steganalysis methods.In addition,the proposed algorithm has excellent performance in visual quality and coding efficiency,and can be applied to practical scenarios of video covert communication.
