In recent years, the nearest neighbor search （NNS） problem has been widely used in various interesting applications. Locality-sensitive hashing （LSH）, a popular algorithm for the approximate nearest neighbor probl...In recent years, the nearest neighbor search （NNS） problem has been widely used in various interesting applications. Locality-sensitive hashing （LSH）, a popular algorithm for the approximate nearest neighbor problem, is proved to be an efficient method to solve the NNS problem in the high-dimensional and large-scale databases. Based on the scheme of p-stable LSH, this paper introduces a novel improvement algorithm called randomness-based locality-sensitive hashing （RLSH） based on p-stable LSH. Our proposed algorithm modifies the query strategy that it randomly selects a certain hash table to project the query point instead of mapping the query point into all hash tables in the period of the nearest neighbor query and reconstructs the candidate points for finding the nearest neighbors. This improvement strategy ensures that RLSH spends less time searching for the nearest neighbors than the p-stable LSH algorithm to keep a high recall. Besides, this strategy is proved to promote the diversity of the candidate points even with fewer hash tables. Experiments are executed on the synthetic dataset and open dataset. The results show that our method can cost less time consumption and less space requirements than the p-stable LSH while balancing the same recall.展开更多
This paper introduces a novel trust-aware hybrid recommendation framework that combines Locality-Sensitive Hashing(LSH)with the trust information in social networks,aiming to provide efficient and effective recommenda...This paper introduces a novel trust-aware hybrid recommendation framework that combines Locality-Sensitive Hashing(LSH)with the trust information in social networks,aiming to provide efficient and effective recommendations.Unlike traditional recommender systems which often overlook the critical influence of user trust,our proposed approach infuses trust metrics to better approximate user preferences.The LSH,with its intrinsic advantage in handling high-dimensional data and computational efficiency,is applied to expedite the process of finding similar items or users.We innovatively adapt LSH to form trust-aware buckets,encapsulating both trust and similarity information.These enhancements mitigate the sparsity and scalability issues usually found in existing recommender systems.Experimental results on a real-world dataset confirm the superiority of our approach in terms of recommendation quality and computational performance.The paper further discusses potential applications and future directions of the trust-aware hybrid recommendation with LSH.展开更多
Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third...Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third-party providers is not always guaranteed. To safeguard against the exposure and misuse of personal privacy information, and achieve secure and efficient retrieval, a secure medical image retrieval based on a multi-attention mechanism and triplet deep hashing is proposed in this paper (abbreviated as MATDH). Specifically, this method first utilizes the contrast-limited adaptive histogram equalization method applicable to color images to enhance chest X-ray images. Next, a designed multi-attention mechanism focuses on important local features during the feature extraction stage. Moreover, a triplet loss function is utilized to learn discriminative hash codes to construct a compact and efficient triplet deep hashing. Finally, upsampling is used to restore the original resolution of the images during retrieval, thereby enabling more accurate matching. To ensure the security of medical image data, a lightweight image encryption method based on frequency domain encryption is designed to encrypt the chest X-ray images. The findings of the experiment indicate that, in comparison to various advanced image retrieval techniques, the suggested approach improves the precision of feature extraction and retrieval using the COVIDx dataset. Additionally, it offers enhanced protection for the confidentiality of medical images stored in cloud settings and demonstrates strong practicality.展开更多
With the growing penetration of wind power in power systems, more accurate prediction of wind speed and wind power is required for real-time scheduling and operation. In this paper, a novel forecast model for shortter...With the growing penetration of wind power in power systems, more accurate prediction of wind speed and wind power is required for real-time scheduling and operation. In this paper, a novel forecast model for shortterm prediction of wind speed and wind power is proposed,which is based on singular spectrum analysis(SSA) and locality-sensitive hashing(LSH). To deal with the impact of high volatility of the original time series, SSA is applied to decompose it into two components: the mean trend,which represents the mean tendency of the original time series, and the fluctuation component, which reveals the stochastic characteristics. Both components are reconstructed in a phase space to obtain mean trend segments and fluctuation component segments. After that, LSH is utilized to select similar segments of the mean trend segments, which are then employed in local forecasting, so that the accuracy and efficiency of prediction can be enhanced. Finally, support vector regression is adopted forprediction, where the training input is the synthesis of the similar mean trend segments and the corresponding fluctuation component segments. Simulation studies are conducted on wind speed and wind power time series from four databases, and the final results demonstrate that the proposed model is more accurate and stable in comparison with other models.展开更多
Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a s...Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a significant problem.The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest.Therefore,several approaches,including steganography,have been developed by researchers over time to enable safe data transit.In this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,etc.We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)approach.In this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this strategy.Before encoding the data and embedding it into a carry image,this review verifies that it has been encrypted.Usually,embedded text in photos conveys crucial signals about the content.This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport.If the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.展开更多
As quantum computing continues to advance,traditional cryptographic methods are increasingly challenged,particularly when it comes to securing critical systems like Supervisory Control andData Acquisition(SCADA)system...As quantum computing continues to advance,traditional cryptographic methods are increasingly challenged,particularly when it comes to securing critical systems like Supervisory Control andData Acquisition(SCADA)systems.These systems are essential for monitoring and controlling industrial operations,making their security paramount.A key threat arises from Shor’s algorithm,a powerful quantum computing tool that can compromise current hash functions,leading to significant concerns about data integrity and confidentiality.To tackle these issues,this article introduces a novel Quantum-Resistant Hash Algorithm(QRHA)known as the Modular Hash Learning Algorithm(MHLA).This algorithm is meticulously crafted to withstand potential quantum attacks by incorporating advanced mathematical and algorithmic techniques,enhancing its overall security framework.Our research delves into the effectiveness ofMHLA in defending against both traditional and quantum-based threats,with a particular emphasis on its resilience to Shor’s algorithm.The findings from our study demonstrate that MHLA significantly enhances the security of SCADA systems in the context of quantum technology.By ensuring that sensitive data remains protected and confidential,MHLA not only fortifies individual systems but also contributes to the broader efforts of safeguarding industrial and infrastructure control systems against future quantumthreats.Our evaluation demonstrates that MHLA improves security by 38%against quantumattack simulations compared to traditional hash functionswhilemaintaining a computational efficiency ofO(m⋅n⋅k+v+n).The algorithm achieved a 98%success rate in detecting data tampering during integrity testing.These findings underline MHLA’s effectiveness in enhancing SCADA system security amidst evolving quantum technologies.This research represents a crucial step toward developing more secure cryptographic systems that can adapt to the rapidly changing technological landscape,ultimately ensuring the reliability and integrity of critical infrastructure in an era where quantum computing poses a growing risk.展开更多
The immutability is a crucial property for blockchain applications,however,it also leads to problems such as the inability to revise illegal data on the blockchain and delete private data.Although redactable blockchai...The immutability is a crucial property for blockchain applications,however,it also leads to problems such as the inability to revise illegal data on the blockchain and delete private data.Although redactable blockchains enable on-chain modification,they suffer from inefficiency and excessive centralization,the majority of redactable blockchain schemes ignore the difficult problems of traceability and consistency check.In this paper,we present a Dynamically Redactable Blockchain based on decentralized Chameleon hash(DRBC).Specifically,we propose an Identity-Based Decentralized Chameleon Hash(IDCH)and a Version-Based Transaction structure(VT)to realize the traceability of transaction modifications in a decentralized environment.Then,we propose an efficient block consistency check protocol based on the Bloom filter tree,which can realize the consistency check of transactions with extremely low time and space cost.Security analysis and experiment results demonstrate the reliability of DRBC and its significant advantages in a decentralized environment.展开更多
Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sam...Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.展开更多
The easy generation, storage, transmission and reproduction of digital images have caused serious abuse and security problems. Assurance of the rightful ownership, integrity, and authenticity is a major concern to the...The easy generation, storage, transmission and reproduction of digital images have caused serious abuse and security problems. Assurance of the rightful ownership, integrity, and authenticity is a major concern to the academia as well as the industry. On the other hand, efficient search of the huge amount of images has become a great challenge. Image hashing is a technique suitable for use in image authentication and content based image retrieval （CBIR）. In this article, we review some representative image hashing techniques proposed in the recent years, with emphases on how to meet the conflicting requirements of perceptual robustness and security. Following a brief introduction to some earlier methods, we focus on a typical two-stage structure and some geometric-distortion resilient techniques. We then introduce two image hashing approaches developed in our own research, and reveal security problems in some existing methods due to the absence of secret keys in certain stage of the image feature extraction, or availability of a large quantity of images, keys, or the hash function to the adversary. More research efforts are needed in developing truly robust and secure image hashing techniques.展开更多
There is a steep increase in data encoded as symmetric positive definite(SPD)matrix in the past decade.The set of SPD matrices forms a Riemannian manifold that constitutes a half convex cone in the vector space of mat...There is a steep increase in data encoded as symmetric positive definite(SPD)matrix in the past decade.The set of SPD matrices forms a Riemannian manifold that constitutes a half convex cone in the vector space of matrices,which we sometimes call SPD manifold.One of the fundamental problems in the application of SPD manifold is to find the nearest neighbor of a queried SPD matrix.Hashing is a popular method that can be used for the nearest neighbor search.However,hashing cannot be directly applied to SPD manifold due to its non-Euclidean intrinsic geometry.Inspired by the idea of kernel trick,a new hashing scheme for SPD manifold by random projection and quantization in expanded data space is proposed in this paper.Experimental results in large scale nearduplicate image detection show the effectiveness and efficiency of the proposed method.展开更多
Image hashing is a useful multimedia technology for many applications,such as image authentication,image retrieval,image copy detection and image forensics.In this paper,we propose a robust image hashing based on rand...Image hashing is a useful multimedia technology for many applications,such as image authentication,image retrieval,image copy detection and image forensics.In this paper,we propose a robust image hashing based on random Gabor filtering and discrete wavelet transform(DWT).Specifically,robust and secure image features are first extracted from the normalized image by Gabor filtering and a chaotic map called Skew tent map,and then are compressed via a single-level 2-D DWT.Image hash is finally obtained by concatenating DWT coefficients in the LL sub-band.Many experiments with open image datasets are carried out and the results illustrate that our hashing is robust,discriminative and secure.Receiver operating characteristic(ROC)curve comparisons show that our hashing is better than some popular image hashing algorithms in classification performance between robustness and discrimination.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.61173143)the Special Public Sector Research Program of China(Grant No.GYHY201206030)the Deanship of Scientific Research at King Saud University for funding this work through research group No.RGP-VPP-264
文摘In recent years, the nearest neighbor search （NNS） problem has been widely used in various interesting applications. Locality-sensitive hashing （LSH）, a popular algorithm for the approximate nearest neighbor problem, is proved to be an efficient method to solve the NNS problem in the high-dimensional and large-scale databases. Based on the scheme of p-stable LSH, this paper introduces a novel improvement algorithm called randomness-based locality-sensitive hashing （RLSH） based on p-stable LSH. Our proposed algorithm modifies the query strategy that it randomly selects a certain hash table to project the query point instead of mapping the query point into all hash tables in the period of the nearest neighbor query and reconstructs the candidate points for finding the nearest neighbors. This improvement strategy ensures that RLSH spends less time searching for the nearest neighbors than the p-stable LSH algorithm to keep a high recall. Besides, this strategy is proved to promote the diversity of the candidate points even with fewer hash tables. Experiments are executed on the synthetic dataset and open dataset. The results show that our method can cost less time consumption and less space requirements than the p-stable LSH while balancing the same recall.
文摘This paper introduces a novel trust-aware hybrid recommendation framework that combines Locality-Sensitive Hashing(LSH)with the trust information in social networks,aiming to provide efficient and effective recommendations.Unlike traditional recommender systems which often overlook the critical influence of user trust,our proposed approach infuses trust metrics to better approximate user preferences.The LSH,with its intrinsic advantage in handling high-dimensional data and computational efficiency,is applied to expedite the process of finding similar items or users.We innovatively adapt LSH to form trust-aware buckets,encapsulating both trust and similarity information.These enhancements mitigate the sparsity and scalability issues usually found in existing recommender systems.Experimental results on a real-world dataset confirm the superiority of our approach in terms of recommendation quality and computational performance.The paper further discusses potential applications and future directions of the trust-aware hybrid recommendation with LSH.
基金supported by the NationalNatural Science Foundation of China(No.61862041).
文摘Medical institutions frequently utilize cloud servers for storing digital medical imaging data, aiming to lower both storage expenses and computational expenses. Nevertheless, the reliability of cloud servers as third-party providers is not always guaranteed. To safeguard against the exposure and misuse of personal privacy information, and achieve secure and efficient retrieval, a secure medical image retrieval based on a multi-attention mechanism and triplet deep hashing is proposed in this paper (abbreviated as MATDH). Specifically, this method first utilizes the contrast-limited adaptive histogram equalization method applicable to color images to enhance chest X-ray images. Next, a designed multi-attention mechanism focuses on important local features during the feature extraction stage. Moreover, a triplet loss function is utilized to learn discriminative hash codes to construct a compact and efficient triplet deep hashing. Finally, upsampling is used to restore the original resolution of the images during retrieval, thereby enabling more accurate matching. To ensure the security of medical image data, a lightweight image encryption method based on frequency domain encryption is designed to encrypt the chest X-ray images. The findings of the experiment indicate that, in comparison to various advanced image retrieval techniques, the suggested approach improves the precision of feature extraction and retrieval using the COVIDx dataset. Additionally, it offers enhanced protection for the confidentiality of medical images stored in cloud settings and demonstrates strong practicality.
基金supported by the Guangdong Innovative Research Team Program(No.201001N0104744201)the State Key Program of the National Natural Science Foundation of China(No.51437006)
文摘With the growing penetration of wind power in power systems, more accurate prediction of wind speed and wind power is required for real-time scheduling and operation. In this paper, a novel forecast model for shortterm prediction of wind speed and wind power is proposed,which is based on singular spectrum analysis(SSA) and locality-sensitive hashing(LSH). To deal with the impact of high volatility of the original time series, SSA is applied to decompose it into two components: the mean trend,which represents the mean tendency of the original time series, and the fluctuation component, which reveals the stochastic characteristics. Both components are reconstructed in a phase space to obtain mean trend segments and fluctuation component segments. After that, LSH is utilized to select similar segments of the mean trend segments, which are then employed in local forecasting, so that the accuracy and efficiency of prediction can be enhanced. Finally, support vector regression is adopted forprediction, where the training input is the synthesis of the similar mean trend segments and the corresponding fluctuation component segments. Simulation studies are conducted on wind speed and wind power time series from four databases, and the final results demonstrate that the proposed model is more accurate and stable in comparison with other models.
文摘Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a significant problem.The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest.Therefore,several approaches,including steganography,have been developed by researchers over time to enable safe data transit.In this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,etc.We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)approach.In this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this strategy.Before encoding the data and embedding it into a carry image,this review verifies that it has been encrypted.Usually,embedded text in photos conveys crucial signals about the content.This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport.If the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.
基金Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R343),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabiathe Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia for funding this research work through the project number NBU-FFR-2025-1092-10.
文摘As quantum computing continues to advance,traditional cryptographic methods are increasingly challenged,particularly when it comes to securing critical systems like Supervisory Control andData Acquisition(SCADA)systems.These systems are essential for monitoring and controlling industrial operations,making their security paramount.A key threat arises from Shor’s algorithm,a powerful quantum computing tool that can compromise current hash functions,leading to significant concerns about data integrity and confidentiality.To tackle these issues,this article introduces a novel Quantum-Resistant Hash Algorithm(QRHA)known as the Modular Hash Learning Algorithm(MHLA).This algorithm is meticulously crafted to withstand potential quantum attacks by incorporating advanced mathematical and algorithmic techniques,enhancing its overall security framework.Our research delves into the effectiveness ofMHLA in defending against both traditional and quantum-based threats,with a particular emphasis on its resilience to Shor’s algorithm.The findings from our study demonstrate that MHLA significantly enhances the security of SCADA systems in the context of quantum technology.By ensuring that sensitive data remains protected and confidential,MHLA not only fortifies individual systems but also contributes to the broader efforts of safeguarding industrial and infrastructure control systems against future quantumthreats.Our evaluation demonstrates that MHLA improves security by 38%against quantumattack simulations compared to traditional hash functionswhilemaintaining a computational efficiency ofO(m⋅n⋅k+v+n).The algorithm achieved a 98%success rate in detecting data tampering during integrity testing.These findings underline MHLA’s effectiveness in enhancing SCADA system security amidst evolving quantum technologies.This research represents a crucial step toward developing more secure cryptographic systems that can adapt to the rapidly changing technological landscape,ultimately ensuring the reliability and integrity of critical infrastructure in an era where quantum computing poses a growing risk.
基金supported in part by the National Key R&D Program of China under project 2022YFB2702901the Guangxi Natural Science Foundation under grants 2024GXNSFDA010064 and 2024GXNSFAA010453+5 种基金the National Natural Science Foundation of China under projects 62172119,62362013,U21A20467 and 72192801Zhejiang Provincial Natural Science Foundation of China under grant LZ23F020012Innovation Project of GUET Graduate Education under grants 2023YCXS070the Guangxi Young Teachers'Basic Ability Improvement Program under grant 2024KY0224Lion Rock Labs of Cyberspace Security under grant LRL24-1-C003one of the research outcomes of the Xiong'an Autonomous and Controllable Blockchain Underlying Technology Platform Project(2020).
文摘The immutability is a crucial property for blockchain applications,however,it also leads to problems such as the inability to revise illegal data on the blockchain and delete private data.Although redactable blockchains enable on-chain modification,they suffer from inefficiency and excessive centralization,the majority of redactable blockchain schemes ignore the difficult problems of traceability and consistency check.In this paper,we present a Dynamically Redactable Blockchain based on decentralized Chameleon hash(DRBC).Specifically,we propose an Identity-Based Decentralized Chameleon Hash(IDCH)and a Version-Based Transaction structure(VT)to realize the traceability of transaction modifications in a decentralized environment.Then,we propose an efficient block consistency check protocol based on the Bloom filter tree,which can realize the consistency check of transactions with extremely low time and space cost.Security analysis and experiment results demonstrate the reliability of DRBC and its significant advantages in a decentralized environment.
基金supported by Hainan Provincial Natural Science Foundation of China(No.524RC532)Research Startup Funding from Hainan Institute of Zhejiang University(No.0210-6602-A12202)Project of Sanya Yazhou Bay Science and Technology City(No.SKJC-2022-PTDX-009/010/011).
文摘Given the rapid development of advanced information systems,microgrids(MGs)suffer from more potential attacks that affect their operational performance.Conventional distributed secondary control with a small,fixed sampling time period inevitably causes the wasteful use of communication resources.This paper proposes a self-triggered secondary control scheme under perturbations from false data injection(FDI)attacks.We designed a linear clock for each DG to trigger its controller at aperiodic and intermittent instants.Sub-sequently,a hash-based defense mechanism(HDM)is designed for detecting and eliminating malicious data infiltrated in the MGs.With the aid of HDM,a self-triggered control scheme achieves the secondary control objectives even in the presence of FDI attacks.Rigorous theoretical analyses and simulation results indicate that the introduced secondary control scheme significantly reduces communication costs and enhances the resilience of MGs under FDI attacks.
基金supported by the National Natural Science Foundation of China（Grant No.60502039）,the Shanghai Rising-Star Program（Grant No.06QA14022）,and the Key project of Shanghai Municipality for Basic Research （Grant No.04JC14037）
文摘The easy generation, storage, transmission and reproduction of digital images have caused serious abuse and security problems. Assurance of the rightful ownership, integrity, and authenticity is a major concern to the academia as well as the industry. On the other hand, efficient search of the huge amount of images has become a great challenge. Image hashing is a technique suitable for use in image authentication and content based image retrieval （CBIR）. In this article, we review some representative image hashing techniques proposed in the recent years, with emphases on how to meet the conflicting requirements of perceptual robustness and security. Following a brief introduction to some earlier methods, we focus on a typical two-stage structure and some geometric-distortion resilient techniques. We then introduce two image hashing approaches developed in our own research, and reveal security problems in some existing methods due to the absence of secret keys in certain stage of the image feature extraction, or availability of a large quantity of images, keys, or the hash function to the adversary. More research efforts are needed in developing truly robust and secure image hashing techniques.
文摘There is a steep increase in data encoded as symmetric positive definite(SPD)matrix in the past decade.The set of SPD matrices forms a Riemannian manifold that constitutes a half convex cone in the vector space of matrices,which we sometimes call SPD manifold.One of the fundamental problems in the application of SPD manifold is to find the nearest neighbor of a queried SPD matrix.Hashing is a popular method that can be used for the nearest neighbor search.However,hashing cannot be directly applied to SPD manifold due to its non-Euclidean intrinsic geometry.Inspired by the idea of kernel trick,a new hashing scheme for SPD manifold by random projection and quantization in expanded data space is proposed in this paper.Experimental results in large scale nearduplicate image detection show the effectiveness and efficiency of the proposed method.
基金This work is partially supported by the National Natural Science Foundation of China(Nos.61562007,61762017,61702332)National Key R&D Plan of China(2018YFB1003701)+3 种基金Guangxi“Bagui Scholar”Teams for Innovation and Research,the Guangxi Natural Science Foundation(Nos.2017GXNSFAA198222,2015GXNSFDA139040)the Project of Guangxi Science and Technology(Nos.GuiKeAD17195062)the Project of the Guangxi Key Lab of Multi-source Information Mining&Security(Nos.16-A-02-02,15-A-02-02)the Guangxi Collaborative Innovation Center of Multi-source Information Integration and Intelligent Processing,and the Innovation Project of Guangxi Graduate Education(No.XYCSZ 2018076).
文摘Image hashing is a useful multimedia technology for many applications,such as image authentication,image retrieval,image copy detection and image forensics.In this paper,we propose a robust image hashing based on random Gabor filtering and discrete wavelet transform(DWT).Specifically,robust and secure image features are first extracted from the normalized image by Gabor filtering and a chaotic map called Skew tent map,and then are compressed via a single-level 2-D DWT.Image hash is finally obtained by concatenating DWT coefficients in the LL sub-band.Many experiments with open image datasets are carried out and the results illustrate that our hashing is robust,discriminative and secure.Receiver operating characteristic(ROC)curve comparisons show that our hashing is better than some popular image hashing algorithms in classification performance between robustness and discrimination.
