Data hiding(DH)is an important technology for securely transmitting secret data in networks,and has increasing become a research hotspot throughout the world.However,for Joint photographic experts group(JPEG)images,it...Data hiding(DH)is an important technology for securely transmitting secret data in networks,and has increasing become a research hotspot throughout the world.However,for Joint photographic experts group(JPEG)images,it is difficult to balance the contradiction among embedded capacity,visual quality and the file size increment in existing data hiding schemes.Thus,to deal with this problem,a high-imperceptibility data hiding for JPEG images is proposed based on direction modification.First,this proposed scheme sorts all of the quantized discrete cosine transform(DCT)block in ascending order according to the number of non-consecutive-zero alternating current(AC)coefficients.Then it selects non-consecutive-zero AC coefficients with absolute values less than or equal to 1 at the same frequency position in two adjacent blocks for pairing.Finally,the 2-bit secret data can be embedded into a coefficient-pair by using the filled reference matrix and the designed direction modification rules.The experiment was conducted on 5 standard test images and 1000 images of BOSSbase dataset,respectively.The experimental results showed that the visual quality of the proposed scheme was improved by 1∼4 dB compared with the comparison schemes,and the file size increment was reduced at most to 15%of the comparison schemes.展开更多
A privacy-preserving search model for JPEG images is proposed in paper,which uses the bag-of-encrypted-words based on QDCT(Quaternion Discrete Cosine Transform)encoding.The JPEG image is obtained by a series of steps ...A privacy-preserving search model for JPEG images is proposed in paper,which uses the bag-of-encrypted-words based on QDCT(Quaternion Discrete Cosine Transform)encoding.The JPEG image is obtained by a series of steps such as DCT(Discrete Cosine Transform)transformation,quantization,entropy coding,etc.In this paper,we firstly transform the images from spatial domain into quaternion domain.By analyzing the algebraic relationship between QDCT and DCT,a QDCT quantization table and QDTC coding for color images are proposed.Then the compressed image data is encrypted after the steps of block permutation,intra-block permutation,single table substitution and stream cipher.At last,the similarity between original image and query image can be measured by the Manhattan distance,which is calculated by two feature vectors with the model of bag-of-words on the cloud server side.The outcome shows good performance in security attack and retrieval accuracy.展开更多
As the wide application of imaging technology,the number of big image data which may containing private information is growing fast.Due to insufficient computing power and storage space for local server device,many pe...As the wide application of imaging technology,the number of big image data which may containing private information is growing fast.Due to insufficient computing power and storage space for local server device,many people hand over these images to cloud servers for management.But actually,it is unsafe to store the images to the cloud,so encryption becomes a necessary step before uploading to reduce the risk of privacy leakage.However,it is not conducive to the efficient application of image,especially in the Content-Based Image Retrieval(CBIR)scheme.This paper proposes an outsourcing privacy-preserving JPEG CBIR scheme.We design a set of JPEG format-compatible encryption method,making no file expansion to JPEG files.We firstly combine multiple adjacent 8×8 DCT coefficient blocks into big-blocks.Then,random scrambling and stream encryption are used on the binary code of DCT coefficients to protect the JPEG image privacy.The task of extracting features from encrypted images and retrieving similar images are done by the cloud server.The group index histograms of DCT coefficients are extracted from the encrypted big-blocks,then the global vector is produced to represent the JPEG image with the aid of bag-of-words(BOW)model.The security analysis and experimental results show that our proposed scheme has strong security and good retrieval performance.展开更多
Reversible watermarking has extensive applications in fields such as medical data management and forensic enforcement. In this article, we propose a modified reverse zero-run length （RZL） coding method for reversibl...Reversible watermarking has extensive applications in fields such as medical data management and forensic enforcement. In this article, we propose a modified reverse zero-run length （RZL） coding method for reversible watermarking, which intro- duces fewer modifications to cover than previous ones under the same embedding rate. By combining the coding method with his- togram shift and quantization table modification strategy, we pro- pose a novel reversible data hiding algorithm for JPEG images. Compared with previous art, when embedding the same payload, our method has an improvement of at least 2 dB in stego image＇s quality, which proves the effectiveness and advantage of our algo- rithm.展开更多
In this paper, we are proposing a compression-based multiple color target detection for practical near real-time optical pattern recognition applications. By reducing the size of the color images to its utmost compres...In this paper, we are proposing a compression-based multiple color target detection for practical near real-time optical pattern recognition applications. By reducing the size of the color images to its utmost compression, the speed and the storage of the system are greatly increased. We have used the powerful Fringe-adjusted joint transform correlation technique to successfully detect compression-based multiple targets in colored images. The colored image is decomposed into three fundamental color components images (Red, Green, Blue) and they are separately processed by three-channel correlators. The outputs of the three channels are then combined into a single correlation output. To eliminate the false alarms and zero-order terms due to multiple desired and undesired targets in a scene, we have used the reference shifted phase-encoded and the reference phase-encoded techniques. The performance of the proposed compression-based technique is assessed through many computer simulation tests for images polluted by strong additive Gaussian and Salt & Pepper noises as well as reference occluded images. The robustness of the scheme is demonstrated for severely compressed images (up to 94% ratio), strong noise densities (up to 0.5), and large reference occlusion images (up to 75%).展开更多
The goal of steganalysis is to detect whether the cover carries the secret information which is embedded by steganographic algorithms.The traditional ste-ganalysis detector is trained on the stego images created by a ...The goal of steganalysis is to detect whether the cover carries the secret information which is embedded by steganographic algorithms.The traditional ste-ganalysis detector is trained on the stego images created by a certain type of ste-ganographic algorithm,whose detection performance drops rapidly when it is applied to detect another type of steganographic algorithm.This phenomenon is called as steganographic algorithm mismatch in steganalysis.To resolve this pro-blem,we propose a deep learning driven feature-based approach.An advanced steganalysis neural network is used to extract steganographic features,different pairs of training images embedded with steganographic algorithms can obtain diverse features of each algorithm.Then a multi-classifier implemented as lightgbm is used to predict the matching algorithm.Experimental results on four types of JPEG steganographic algorithms prove that the proposed method can improve the detection accuracy in the scenario of steganographic algorithm mismatch.展开更多
基金supported by the National Natural Science Foundation of China (62072325)Shanxi Scholarship Council of China (HGKY2019081)+1 种基金Fundamental Research Program of Shanxi Province (202103021224272)TYUST SRIF (20212039).
文摘Data hiding(DH)is an important technology for securely transmitting secret data in networks,and has increasing become a research hotspot throughout the world.However,for Joint photographic experts group(JPEG)images,it is difficult to balance the contradiction among embedded capacity,visual quality and the file size increment in existing data hiding schemes.Thus,to deal with this problem,a high-imperceptibility data hiding for JPEG images is proposed based on direction modification.First,this proposed scheme sorts all of the quantized discrete cosine transform(DCT)block in ascending order according to the number of non-consecutive-zero alternating current(AC)coefficients.Then it selects non-consecutive-zero AC coefficients with absolute values less than or equal to 1 at the same frequency position in two adjacent blocks for pairing.Finally,the 2-bit secret data can be embedded into a coefficient-pair by using the filled reference matrix and the designed direction modification rules.The experiment was conducted on 5 standard test images and 1000 images of BOSSbase dataset,respectively.The experimental results showed that the visual quality of the proposed scheme was improved by 1∼4 dB compared with the comparison schemes,and the file size increment was reduced at most to 15%of the comparison schemes.
基金This work is supported in part by the Jiangsu Basic Research Programs-Natural Science Foundation under grant numbers BK20181407in part by the National Natural Science Foundation of China under grant numbers U1936118,61672294+3 种基金in part by Six peak talent project of Jiangsu Province(R2016L13)Qinglan Project of Jiangsu Province,and“333”project of Jiangsu Province,in part by the National Natural Science Foundation of China under grant numbers U1836208,61702276,61772283,61602253,and 61601236in part by National Key R\&D Program of China under grant 2018YFB1003205in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)fund,in part by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)fund,China.Zhihua Xia is supported by BK21+program from the Ministry of Education of Korea.
文摘A privacy-preserving search model for JPEG images is proposed in paper,which uses the bag-of-encrypted-words based on QDCT(Quaternion Discrete Cosine Transform)encoding.The JPEG image is obtained by a series of steps such as DCT(Discrete Cosine Transform)transformation,quantization,entropy coding,etc.In this paper,we firstly transform the images from spatial domain into quaternion domain.By analyzing the algebraic relationship between QDCT and DCT,a QDCT quantization table and QDTC coding for color images are proposed.Then the compressed image data is encrypted after the steps of block permutation,intra-block permutation,single table substitution and stream cipher.At last,the similarity between original image and query image can be measured by the Manhattan distance,which is calculated by two feature vectors with the model of bag-of-words on the cloud server side.The outcome shows good performance in security attack and retrieval accuracy.
基金This work is supported in part by the Jiangsu Basic Research Programs-Natural Science Foundation under Grant No.BK20181407in part by the National Natural Science Foundation of China under Grant Nos.U1936118,61672294+4 种基金in part by Six Peak Talent Project of Jiangsu Province(R2016L13)Qinglan Project of Jiangsu Province,and“333”Project of Jiangsu Province,in part by the National Natural Science Foundation of China under Grant Nos.U1836208,61702276,61772283,61602253,and 61601236in part by National Key R&D Program of China under Grant No.2018YFB1003205in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)Fundin part by the Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET)Fund,China.Zhihua Xia is supported by BK21+Program from the Ministry of Education of Korea.
文摘As the wide application of imaging technology,the number of big image data which may containing private information is growing fast.Due to insufficient computing power and storage space for local server device,many people hand over these images to cloud servers for management.But actually,it is unsafe to store the images to the cloud,so encryption becomes a necessary step before uploading to reduce the risk of privacy leakage.However,it is not conducive to the efficient application of image,especially in the Content-Based Image Retrieval(CBIR)scheme.This paper proposes an outsourcing privacy-preserving JPEG CBIR scheme.We design a set of JPEG format-compatible encryption method,making no file expansion to JPEG files.We firstly combine multiple adjacent 8×8 DCT coefficient blocks into big-blocks.Then,random scrambling and stream encryption are used on the binary code of DCT coefficients to protect the JPEG image privacy.The task of extracting features from encrypted images and retrieving similar images are done by the cloud server.The group index histograms of DCT coefficients are extracted from the encrypted big-blocks,then the global vector is produced to represent the JPEG image with the aid of bag-of-words(BOW)model.The security analysis and experimental results show that our proposed scheme has strong security and good retrieval performance.
基金Supported by the National Natural Science Foundation of China(61170234and60803155)the National Science and Technology Major Project of China(2010ZX03004-003)the High-Tech Research and Development Program of China(863program)(2009AA012201)
文摘Reversible watermarking has extensive applications in fields such as medical data management and forensic enforcement. In this article, we propose a modified reverse zero-run length （RZL） coding method for reversible watermarking, which intro- duces fewer modifications to cover than previous ones under the same embedding rate. By combining the coding method with his- togram shift and quantization table modification strategy, we pro- pose a novel reversible data hiding algorithm for JPEG images. Compared with previous art, when embedding the same payload, our method has an improvement of at least 2 dB in stego image＇s quality, which proves the effectiveness and advantage of our algo- rithm.
文摘In this paper, we are proposing a compression-based multiple color target detection for practical near real-time optical pattern recognition applications. By reducing the size of the color images to its utmost compression, the speed and the storage of the system are greatly increased. We have used the powerful Fringe-adjusted joint transform correlation technique to successfully detect compression-based multiple targets in colored images. The colored image is decomposed into three fundamental color components images (Red, Green, Blue) and they are separately processed by three-channel correlators. The outputs of the three channels are then combined into a single correlation output. To eliminate the false alarms and zero-order terms due to multiple desired and undesired targets in a scene, we have used the reference shifted phase-encoded and the reference phase-encoded techniques. The performance of the proposed compression-based technique is assessed through many computer simulation tests for images polluted by strong additive Gaussian and Salt & Pepper noises as well as reference occluded images. The robustness of the scheme is demonstrated for severely compressed images (up to 94% ratio), strong noise densities (up to 0.5), and large reference occlusion images (up to 75%).
基金supported by the National Natural Science Foundation of China (NSFC)under grant No.U1836102Anhui Science and Technology Key Special Program under the grant No.201903a050200162020 Domestic Visiting and Training Program for Outstanding Young Backbone Talents in Colleges and Universities under the grant No.gxgnfx2020132.
文摘The goal of steganalysis is to detect whether the cover carries the secret information which is embedded by steganographic algorithms.The traditional ste-ganalysis detector is trained on the stego images created by a certain type of ste-ganographic algorithm,whose detection performance drops rapidly when it is applied to detect another type of steganographic algorithm.This phenomenon is called as steganographic algorithm mismatch in steganalysis.To resolve this pro-blem,we propose a deep learning driven feature-based approach.An advanced steganalysis neural network is used to extract steganographic features,different pairs of training images embedded with steganographic algorithms can obtain diverse features of each algorithm.Then a multi-classifier implemented as lightgbm is used to predict the matching algorithm.Experimental results on four types of JPEG steganographic algorithms prove that the proposed method can improve the detection accuracy in the scenario of steganographic algorithm mismatch.
