The potential of cloud computing,an emerging concept to minimize the costs associated with computing has recently drawn the interest of a number of researchers.The fast advancements in cloud computing techniques led t...The potential of cloud computing,an emerging concept to minimize the costs associated with computing has recently drawn the interest of a number of researchers.The fast advancements in cloud computing techniques led to the amazing arrival of cloud services.But data security is a challenging issue for modern civilization.The main issues with cloud computing are cloud security as well as effective cloud distribution over the network.Increasing the privacy of data with encryption methods is the greatest approach,which has highly progressed in recent times.In this aspect,sanitization is also the process of confidentiality of data.The goal of this work is to present a deep learning-assisted data sanitization procedure for data security.The proposed data sanitization process involves the following steps:data preprocessing,optimal key generation,deep learning-assisted key fine-tuning,and Kronecker product.Here,the data preprocessing considers original data as well as the extracted statistical feature.Key generation is the subsequent process,for which,a self-adaptive Namib beetle optimization(SANBO)algorithm is developed in this research.Among the generated keys,appropriate keys are fine-tuned by the improved Deep Maxout classifier.Then,the Kronecker product is done in the sanitization process.Reversing the sanitization procedure will yield the original data during the data restoration phase.The study part notes that the suggested data sanitization technique guarantees cloud data security against malign attacks.Also,the analysis of proposed work in terms of restoration effectiveness and key sensitivity analysis is also done.展开更多
With cloud computing,large chunks of data can be handled at a small cost.However,there are some reservations regarding the security and privacy of cloud data stored.For solving these issues and enhancing cloud computi...With cloud computing,large chunks of data can be handled at a small cost.However,there are some reservations regarding the security and privacy of cloud data stored.For solving these issues and enhancing cloud computing security,this research provides a Three-Layered Security Access model(TLSA)aligned to an intrusion detection mechanism,access control mechanism,and data encryption system.The TLSA underlines the need for the protection of sensitive data.This proposed approach starts with Layer 1 data encryption using the Advanced Encryption Standard(AES).For data transfer and storage,this encryption guarantees the data’s authenticity and secrecy.Surprisingly,the solution employs the AES encryption algorithm to secure essential data before storing them in the Cloud to minimize unauthorized access.Role-based access control(RBAC)implements the second strategic level,which ensures specific personnel access certain data and resources.In RBAC,each user is allowed a specific role and Permission.This implies that permitted users can access some data stored in the Cloud.This layer assists in filtering granular access to data,reducing the risk that undesired data will be discovered during the process.Layer 3 deals with intrusion detection systems(IDS),which detect and quickly deal with malicious actions and intrusion attempts.The proposed TLSA security model of e-commerce includes conventional levels of security,such as encryption and access control,and encloses an insight intrusion detection system.This method offers integrated solutions for most typical security issues of cloud computing,including data secrecy,method of access,and threats.An extensive performance test was carried out to confirm the efficiency of the proposed three-tier security method.Comparisons have been made with state-of-art techniques,including DES,RSA,and DUAL-RSA,keeping into account Accuracy,QILV,F-Measure,Sensitivity,MSE,PSNR,SSIM,and computation time,encryption time,and decryption time.The proposed TLSA method provides an accuracy of 89.23%,F-Measure of 0.876,and SSIM of 0.8564 at a computation time of 5.7 s.A comparison with existing methods shows the better performance of the proposed method,thus confirming the enhanced ability to address security issues in cloud computing.展开更多
Advanced cloud computing technology provides cost saving and flexibility of services for users.With the explosion of multimedia data,more and more data owners would outsource their personal multimedia data on the clou...Advanced cloud computing technology provides cost saving and flexibility of services for users.With the explosion of multimedia data,more and more data owners would outsource their personal multimedia data on the cloud.In the meantime,some computationally expensive tasks are also undertaken by cloud servers.However,the outsourced multimedia data and its applications may reveal the data owner’s private information because the data owners lose the control of their data.Recently,this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia data.In this paper,two reversible data hiding schemes are proposed for encrypted image data in cloud computing:reversible data hiding by homomorphic encryption and reversible data hiding in encrypted domain.The former is that additional bits are extracted after decryption and the latter is that extracted before decryption.Meanwhile,a combined scheme is also designed.This paper proposes the privacy-preserving outsourcing scheme of reversible data hiding over encrypted image data in cloud computing,which not only ensures multimedia data security without relying on the trustworthiness of cloud servers,but also guarantees that reversible data hiding can be operated over encrypted images at the different stages.Theoretical analysis confirms the correctness of the proposed encryption model and justifies the security of the proposed scheme.The computation cost of the proposed scheme is acceptable and adjusts to different security levels.展开更多
The dissociation between data management and data ownership makes it difficult to protect data security and privacy in cloud storage systems.Traditional encryption technologies are not suitable for data protection in ...The dissociation between data management and data ownership makes it difficult to protect data security and privacy in cloud storage systems.Traditional encryption technologies are not suitable for data protection in cloud storage systems.A novel multi-authority proxy re-encryption mechanism based on ciphertext-policy attribute-based encryption（MPRE-CPABE） is proposed for cloud storage systems.MPRE-CPABE requires data owner to split each file into two blocks,one big block and one small block.The small block is used to encrypt the big one as the private key,and then the encrypted big block will be uploaded to the cloud storage system.Even if the uploaded big block of file is stolen,illegal users cannot get the complete information of the file easily.Ciphertext-policy attribute-based encryption（CPABE）is always criticized for its heavy overload and insecure issues when distributing keys or revoking user＇s access right.MPRE-CPABE applies CPABE to the multi-authority cloud storage system,and solves the above issues.The weighted access structure（WAS） is proposed to support a variety of fine-grained threshold access control policy in multi-authority environments,and reduce the computational cost of key distribution.Meanwhile,MPRE-CPABE uses proxy re-encryption to reduce the computational cost of access revocation.Experiments are implemented on platforms of Ubuntu and CloudSim.Experimental results show that MPRE-CPABE can greatly reduce the computational cost of the generation of key components and the revocation of user＇s access right.MPRE-CPABE is also proved secure under the security model of decisional bilinear Diffie-Hellman（DBDH）.展开更多
文摘The potential of cloud computing,an emerging concept to minimize the costs associated with computing has recently drawn the interest of a number of researchers.The fast advancements in cloud computing techniques led to the amazing arrival of cloud services.But data security is a challenging issue for modern civilization.The main issues with cloud computing are cloud security as well as effective cloud distribution over the network.Increasing the privacy of data with encryption methods is the greatest approach,which has highly progressed in recent times.In this aspect,sanitization is also the process of confidentiality of data.The goal of this work is to present a deep learning-assisted data sanitization procedure for data security.The proposed data sanitization process involves the following steps:data preprocessing,optimal key generation,deep learning-assisted key fine-tuning,and Kronecker product.Here,the data preprocessing considers original data as well as the extracted statistical feature.Key generation is the subsequent process,for which,a self-adaptive Namib beetle optimization(SANBO)algorithm is developed in this research.Among the generated keys,appropriate keys are fine-tuned by the improved Deep Maxout classifier.Then,the Kronecker product is done in the sanitization process.Reversing the sanitization procedure will yield the original data during the data restoration phase.The study part notes that the suggested data sanitization technique guarantees cloud data security against malign attacks.Also,the analysis of proposed work in terms of restoration effectiveness and key sensitivity analysis is also done.
基金funded by UKRI EPSRC Grant EP/W020408/1 Project SPRITE+2:The Security,Privacy,Identity and Trust Engagement Network plus(phase 2)for this studyThe authors also have been funded by PhD project RS718 on Explainable AI through UKRI EPSRC Grant funded Doctoral Training Centre at Swansea University.
文摘With cloud computing,large chunks of data can be handled at a small cost.However,there are some reservations regarding the security and privacy of cloud data stored.For solving these issues and enhancing cloud computing security,this research provides a Three-Layered Security Access model(TLSA)aligned to an intrusion detection mechanism,access control mechanism,and data encryption system.The TLSA underlines the need for the protection of sensitive data.This proposed approach starts with Layer 1 data encryption using the Advanced Encryption Standard(AES).For data transfer and storage,this encryption guarantees the data’s authenticity and secrecy.Surprisingly,the solution employs the AES encryption algorithm to secure essential data before storing them in the Cloud to minimize unauthorized access.Role-based access control(RBAC)implements the second strategic level,which ensures specific personnel access certain data and resources.In RBAC,each user is allowed a specific role and Permission.This implies that permitted users can access some data stored in the Cloud.This layer assists in filtering granular access to data,reducing the risk that undesired data will be discovered during the process.Layer 3 deals with intrusion detection systems(IDS),which detect and quickly deal with malicious actions and intrusion attempts.The proposed TLSA security model of e-commerce includes conventional levels of security,such as encryption and access control,and encloses an insight intrusion detection system.This method offers integrated solutions for most typical security issues of cloud computing,including data secrecy,method of access,and threats.An extensive performance test was carried out to confirm the efficiency of the proposed three-tier security method.Comparisons have been made with state-of-art techniques,including DES,RSA,and DUAL-RSA,keeping into account Accuracy,QILV,F-Measure,Sensitivity,MSE,PSNR,SSIM,and computation time,encryption time,and decryption time.The proposed TLSA method provides an accuracy of 89.23%,F-Measure of 0.876,and SSIM of 0.8564 at a computation time of 5.7 s.A comparison with existing methods shows the better performance of the proposed method,thus confirming the enhanced ability to address security issues in cloud computing.
基金This work was supported by the National Natural Science Foundation of China(No.61702276)the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology under Grant 2016r055 and the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions.The authors are grateful for the anonymous reviewers who made constructive comments and improvements.
文摘Advanced cloud computing technology provides cost saving and flexibility of services for users.With the explosion of multimedia data,more and more data owners would outsource their personal multimedia data on the cloud.In the meantime,some computationally expensive tasks are also undertaken by cloud servers.However,the outsourced multimedia data and its applications may reveal the data owner’s private information because the data owners lose the control of their data.Recently,this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia data.In this paper,two reversible data hiding schemes are proposed for encrypted image data in cloud computing:reversible data hiding by homomorphic encryption and reversible data hiding in encrypted domain.The former is that additional bits are extracted after decryption and the latter is that extracted before decryption.Meanwhile,a combined scheme is also designed.This paper proposes the privacy-preserving outsourcing scheme of reversible data hiding over encrypted image data in cloud computing,which not only ensures multimedia data security without relying on the trustworthiness of cloud servers,but also guarantees that reversible data hiding can be operated over encrypted images at the different stages.Theoretical analysis confirms the correctness of the proposed encryption model and justifies the security of the proposed scheme.The computation cost of the proposed scheme is acceptable and adjusts to different security levels.
基金supported by the National Natural Science Foundation of China(6120200461472192)+1 种基金the Special Fund for Fast Sharing of Science Paper in Net Era by CSTD(2013116)the Natural Science Fund of Higher Education of Jiangsu Province(14KJB520014)
文摘The dissociation between data management and data ownership makes it difficult to protect data security and privacy in cloud storage systems.Traditional encryption technologies are not suitable for data protection in cloud storage systems.A novel multi-authority proxy re-encryption mechanism based on ciphertext-policy attribute-based encryption（MPRE-CPABE） is proposed for cloud storage systems.MPRE-CPABE requires data owner to split each file into two blocks,one big block and one small block.The small block is used to encrypt the big one as the private key,and then the encrypted big block will be uploaded to the cloud storage system.Even if the uploaded big block of file is stolen,illegal users cannot get the complete information of the file easily.Ciphertext-policy attribute-based encryption（CPABE）is always criticized for its heavy overload and insecure issues when distributing keys or revoking user＇s access right.MPRE-CPABE applies CPABE to the multi-authority cloud storage system,and solves the above issues.The weighted access structure（WAS） is proposed to support a variety of fine-grained threshold access control policy in multi-authority environments,and reduce the computational cost of key distribution.Meanwhile,MPRE-CPABE uses proxy re-encryption to reduce the computational cost of access revocation.Experiments are implemented on platforms of Ubuntu and CloudSim.Experimental results show that MPRE-CPABE can greatly reduce the computational cost of the generation of key components and the revocation of user＇s access right.MPRE-CPABE is also proved secure under the security model of decisional bilinear Diffie-Hellman（DBDH）.
