Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner.The advantages of cloud computing is its remote access where data can access...Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner.The advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation(RMI).The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any user.Due to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient service.To improve the performance in data security,the block chains are used for securing the data in the cloud environment.However,the traditional block chain technique are not suitable to provide efficient security to the cloud data stored in the cloud.In this paper,an efficient user centric block level Attribute Based Encryption(UCBL-ABE)scheme is presented to provide the efficient security of cloud data in cloud environment.The proposed approach performs data transaction by employing the block chain.The proposed system provides efficient privacy with access control to the user access according to the behavior of cloud user using Data Level Access Trust(DLAT).Based on DLAT,the user access has been restricted in the cloud environment.The proposed protocol is implemented in real time using Java programming language and uses IBM cloud.The implementation results justifies that the proposed system can able to provide efficient security to the data present in and cloud and also enhances the cloud performance.展开更多
Updatable block-level message-locked encryption(MLE) can efficiently update encrypted data, and public auditing can verify the integrity of cloud storage data by utilizing a third party auditor(TPA). However, there ar...Updatable block-level message-locked encryption(MLE) can efficiently update encrypted data, and public auditing can verify the integrity of cloud storage data by utilizing a third party auditor(TPA). However, there are seldom schemes supporting both updatable block-level deduplication and public auditing. In this paper, an updatable block-level deduplication scheme with efficient auditing is proposed based on a tree-based authenticated structure. In the proposed scheme, the cloud server(CS) can perform block-level deduplication, and the TPA achieves integrity auditing tasks. When a data block is updated, the ciphertext and auditing tags could be updated efficiently. The security analysis demonstrates that the proposed scheme can achieve privacy under chosen distribution attacks in secure deduplication and resist uncheatable chosen distribution attacks(UNC-CDA) in proof of ownership(PoW). Furthermore, the integrity auditing process is proven secure under adaptive chosen-message attacks. Compared with previous relevant schemes, the proposed scheme achieves better functionality and higher efficiency.展开更多
Ciphertext-policy attribute-based searchable encryption （CP-ABSE） can achieve fine-grained access control for data sharing and retrieval, and secure deduplication can save storage space by eliminating duplicate copi...Ciphertext-policy attribute-based searchable encryption （CP-ABSE） can achieve fine-grained access control for data sharing and retrieval, and secure deduplication can save storage space by eliminating duplicate copies. However, there are seldom schemes supporting both searchable encryption and secure deduplication. In this paper, a large universe CP-ABSE scheme supporting secure block-level deduplication are proposed under a hybrid cloud mechanism. In the proposed scheme, after the ciphertext is inserted into bloom filter tree （BFT）, private cloud can perform fine-grained deduplication efficiently by matching tags, and public cloud can search efficiently using homomorphic searchable method and keywords matching. Finally, the proposed scheme can achieve privacy under chosen distribution attacks block-level （PRV-CDA-B） secure deduplication and match-concealing （MC） searchable security. Compared with existing schemes, the proposed scheme has the advantage in supporting fine-grained access control, block-level deduplication and efficient search, simultaneously.展开更多
The video compression sensing method based onmulti hypothesis has attracted extensive attention in the research of video codec with limited resources.However,the formation of high-quality prediction blocks in the mult...The video compression sensing method based onmulti hypothesis has attracted extensive attention in the research of video codec with limited resources.However,the formation of high-quality prediction blocks in the multi hypothesis prediction stage is a challenging task.To resolve this problem,this paper constructs a novel compressed sensing-based high-quality adaptive video reconstruction optimizationmethod.Itmainly includes the optimization of prediction blocks(OPBS),the selection of searchwindows and the use of neighborhood information.Specifically,the OPBS consists of two parts:the selection of blocks and the optimization of prediction blocks.We combine the high-quality optimization reconstruction of foreground block with the residual reconstruction of the background block to improve the overall reconstruction effect of the video sequence.In addition,most of the existing methods based on predictive residual reconstruction ignore the impact of search windows and reference frames on performance.Therefore,Block-level search window(BSW)is constructed to cover the position of the optimal hypothesis block as much as possible.To maximize the availability of reference frames,Nearby reference frame information(NRFI)is designed to reconstruct the current block.The proposed method effectively suppresses the influence of the fluctuation of the prediction block on reconstruction and improves the reconstruction performance.Experimental results showthat the proposed compressed sensing-based high-quality adaptive video reconstruction optimization method significantly improves the reconstruction performance in both objective and supervisor quality.展开更多
文摘Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner.The advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation(RMI).The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any user.Due to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient service.To improve the performance in data security,the block chains are used for securing the data in the cloud environment.However,the traditional block chain technique are not suitable to provide efficient security to the cloud data stored in the cloud.In this paper,an efficient user centric block level Attribute Based Encryption(UCBL-ABE)scheme is presented to provide the efficient security of cloud data in cloud environment.The proposed approach performs data transaction by employing the block chain.The proposed system provides efficient privacy with access control to the user access according to the behavior of cloud user using Data Level Access Trust(DLAT).Based on DLAT,the user access has been restricted in the cloud environment.The proposed protocol is implemented in real time using Java programming language and uses IBM cloud.The implementation results justifies that the proposed system can able to provide efficient security to the data present in and cloud and also enhances the cloud performance.
基金supported by the Doctoral Foundation in Henan University of Technology (31401152)
文摘Updatable block-level message-locked encryption(MLE) can efficiently update encrypted data, and public auditing can verify the integrity of cloud storage data by utilizing a third party auditor(TPA). However, there are seldom schemes supporting both updatable block-level deduplication and public auditing. In this paper, an updatable block-level deduplication scheme with efficient auditing is proposed based on a tree-based authenticated structure. In the proposed scheme, the cloud server(CS) can perform block-level deduplication, and the TPA achieves integrity auditing tasks. When a data block is updated, the ciphertext and auditing tags could be updated efficiently. The security analysis demonstrates that the proposed scheme can achieve privacy under chosen distribution attacks in secure deduplication and resist uncheatable chosen distribution attacks(UNC-CDA) in proof of ownership(PoW). Furthermore, the integrity auditing process is proven secure under adaptive chosen-message attacks. Compared with previous relevant schemes, the proposed scheme achieves better functionality and higher efficiency.
基金supported by the National Natural Science Foundation of China (61472470)the Science and Technology Bureau Project of Weiyang District of Xi’an City (201403)the National Natural Science Foundation of Shaanxi Province (2014JM2-6091, 2015JQ1007)
文摘Ciphertext-policy attribute-based searchable encryption （CP-ABSE） can achieve fine-grained access control for data sharing and retrieval, and secure deduplication can save storage space by eliminating duplicate copies. However, there are seldom schemes supporting both searchable encryption and secure deduplication. In this paper, a large universe CP-ABSE scheme supporting secure block-level deduplication are proposed under a hybrid cloud mechanism. In the proposed scheme, after the ciphertext is inserted into bloom filter tree （BFT）, private cloud can perform fine-grained deduplication efficiently by matching tags, and public cloud can search efficiently using homomorphic searchable method and keywords matching. Finally, the proposed scheme can achieve privacy under chosen distribution attacks block-level （PRV-CDA-B） secure deduplication and match-concealing （MC） searchable security. Compared with existing schemes, the proposed scheme has the advantage in supporting fine-grained access control, block-level deduplication and efficient search, simultaneously.
基金supported by the National Natural Science Foundation of China under Grant No.61806138KeyR&DProgram of Shanxi Province(International Cooperation)under Grant No.201903D421048+1 种基金National Key Research and Development Program of China under Grant No.2018YFC1604000School Level Postgraduate Education Innovation Projects under Grant No.XCX212082.
文摘The video compression sensing method based onmulti hypothesis has attracted extensive attention in the research of video codec with limited resources.However,the formation of high-quality prediction blocks in the multi hypothesis prediction stage is a challenging task.To resolve this problem,this paper constructs a novel compressed sensing-based high-quality adaptive video reconstruction optimizationmethod.Itmainly includes the optimization of prediction blocks(OPBS),the selection of searchwindows and the use of neighborhood information.Specifically,the OPBS consists of two parts:the selection of blocks and the optimization of prediction blocks.We combine the high-quality optimization reconstruction of foreground block with the residual reconstruction of the background block to improve the overall reconstruction effect of the video sequence.In addition,most of the existing methods based on predictive residual reconstruction ignore the impact of search windows and reference frames on performance.Therefore,Block-level search window(BSW)is constructed to cover the position of the optimal hypothesis block as much as possible.To maximize the availability of reference frames,Nearby reference frame information(NRFI)is designed to reconstruct the current block.The proposed method effectively suppresses the influence of the fluctuation of the prediction block on reconstruction and improves the reconstruction performance.Experimental results showthat the proposed compressed sensing-based high-quality adaptive video reconstruction optimization method significantly improves the reconstruction performance in both objective and supervisor quality.
文摘探讨俞募配穴针法联合穴位埋针法治疗风痰闭阻型支气管哮喘的疗效及对血清免疫球蛋白E(Immunoglobin E,IgE)、可溶性二聚体细胞因子(Interferon-γ,IFN-γ)、肺表面活性蛋白(Pulmonary surfactant protein,SP-A)水平影响。方法选取医院收治的风痰闭阻型支气管哮喘患者108例,采用区组随机化原则分为两组各54例。对照组给予穴位埋针法,治疗组在对照组基础上给予俞募配穴针法,两组患者数据观察:对比治疗后临床疗效、哮喘控制测试(Asthma control test,ACT)量表评分、第一秒最大呼气容积(Forced expiratory volume in one second,FEV1)、呼气峰值流速(Peak expiratory,PEF)、用力肺活量(Forced vital capacity,FVC)、临床症状评分及IgE、IFN-γ、SP-A水平、临床治疗安全性及患者满意度。结果经过治疗后,治疗组临床疗效显著较高(P<0.05);两组治疗前ACT评分差异无统计学意义(P>0.05);治疗后两组ACT评分明显升高(P<0.05);且治疗组升高较明显(P<0.05);治疗后两组FEV1、PEF、FVC值明显升高(P<0.05);且治疗组升高较明显(P<0.05);两组治疗前临床症状评分差异无统计学意义(P>0.05);两组治疗后咳嗽、呼吸困难、喘息等症状评分显著降低(P<0.05);且治疗组降低较明显(P<0.05);两组治疗前血清IgE、IFN-γ、SP-A水平无差异(P>0.05);两组治疗后血清IgE显著降低,血清IFN-γ、SP-A水平显著升高(P<0.05);且治疗组改善较明显(P<0.05);治疗组未见治疗不良反应,对照组患者出现1例不良反应,症状为恶心,P>0.05;治疗组治疗满意率高达98.15%(53/54),显著高于对照组的83.33%(45/54),P<0.05。结论采用俞募配穴针法联合穴位埋针法治疗风痰闭阻型支气管哮喘具有较好的治疗效果,能够改善血清IgE、IFN-γ及SP-A水平,且本次治疗安全可靠,患者十分认可,值得在临床上推广应用。
