Due to the development of technology in medicine,millions of health-related data such as scanning the images are generated.It is a great challenge to store the data and handle a massive volume of data.Healthcare data ...Due to the development of technology in medicine,millions of health-related data such as scanning the images are generated.It is a great challenge to store the data and handle a massive volume of data.Healthcare data is stored in the cloud-fog storage environments.This cloud-Fog based health model allows the users to get health-related data from different sources,and duplicated informa-tion is also available in the background.Therefore,it requires an additional sto-rage area,increase in data acquisition time,and insecure data replication in the environment.This paper is proposed to eliminate the de-duplication data using a window size chunking algorithm with a biased sampling-based bloomfilter and provide the health data security using the Advanced Signature-Based Encryp-tion(ASE)algorithm in the Fog-Cloud Environment(WCA-BF+ASE).This WCA-BF+ASE eliminates the duplicate copy of the data and minimizes its sto-rage space and maintenance cost.The data is also stored in an efficient and in a highly secured manner.The security level in the cloud storage environment Win-dows Chunking Algorithm(WSCA)has got 86.5%,two thresholds two divisors(TTTD)80%,Ordinal in Python(ORD)84.4%,Boom Filter(BF)82%,and the proposed work has got better security storage of 97%.And also,after applying the de-duplication process,the proposed method WCA-BF+ASE has required only less storage space for variousfile sizes of 10 KB for 200,400 MB has taken only 22 KB,and 600 MB has required 35 KB,800 MB has consumed only 38 KB,1000 MB has taken 40 KB of storage spaces.展开更多
The sensitive data stored in the public cloud by privileged users,such as corporate companies and government agencies are highly vulnerable in the hands of cloud providers and hackers.The proposed Virtual Cloud Storag...The sensitive data stored in the public cloud by privileged users,such as corporate companies and government agencies are highly vulnerable in the hands of cloud providers and hackers.The proposed Virtual Cloud Storage Archi-tecture is primarily concerned with data integrity and confidentiality,as well as availability.To provide confidentiality and availability,thefile to be stored in cloud storage should be encrypted using an auto-generated key and then encoded into distinct chunks.Hashing the encoded chunks ensured thefile integrity,and a newly proposed Circular Shift Chunk Allocation technique was used to determine the order of chunk storage.Thefile could be retrieved by performing the opera-tions in reverse.Using the regenerating code,the model could regenerate the missing and corrupted chunks from the cloud.The proposed architecture adds an extra layer of security while maintaining a reasonable response time and sto-rage capacity.Experimental results analysis show that the proposed model has been tested with storage space and response time for storage and retrieval.The VCSA model consumes 1.5x(150%)storage space.It was found that total storage required for the VCSA model is very low when compared with 2x Replication and completely satisfies the CIA model.The response time VCSA model was tested with different sizedfiles starting from 2 to 16 MB.The response time for storing and retrieving a 2 MBfile is 4.96 and 3.77 s respectively,and for a 16 MBfile,the response times are 11.06 s for storage and 5.6 s for retrieval.展开更多
本文描述了一个基于分层语块分析的统计翻译模型。该模型在形式上不仅符合同步上下文无关文法,而且融合了基于条件随机场的英文语块分析知识,因此基于分层语块分析的统计翻译模型做到了将句法翻译模型和短语翻译模型有效地结合。该系统...本文描述了一个基于分层语块分析的统计翻译模型。该模型在形式上不仅符合同步上下文无关文法,而且融合了基于条件随机场的英文语块分析知识,因此基于分层语块分析的统计翻译模型做到了将句法翻译模型和短语翻译模型有效地结合。该系统的解码算法改进了线图分析的CKY算法,融入了线性的N-gram语言模型。目前,本文主要针对中文-英文的口语翻译进行了一系列实验,并以国际口语评测IWSLT(International Workshopon Spoken Language Translation)为标准,在2005年的评测测试集上,BLEU和NIST得分均比统计短语翻译系统有所提高。展开更多
文摘Due to the development of technology in medicine,millions of health-related data such as scanning the images are generated.It is a great challenge to store the data and handle a massive volume of data.Healthcare data is stored in the cloud-fog storage environments.This cloud-Fog based health model allows the users to get health-related data from different sources,and duplicated informa-tion is also available in the background.Therefore,it requires an additional sto-rage area,increase in data acquisition time,and insecure data replication in the environment.This paper is proposed to eliminate the de-duplication data using a window size chunking algorithm with a biased sampling-based bloomfilter and provide the health data security using the Advanced Signature-Based Encryp-tion(ASE)algorithm in the Fog-Cloud Environment(WCA-BF+ASE).This WCA-BF+ASE eliminates the duplicate copy of the data and minimizes its sto-rage space and maintenance cost.The data is also stored in an efficient and in a highly secured manner.The security level in the cloud storage environment Win-dows Chunking Algorithm(WSCA)has got 86.5%,two thresholds two divisors(TTTD)80%,Ordinal in Python(ORD)84.4%,Boom Filter(BF)82%,and the proposed work has got better security storage of 97%.And also,after applying the de-duplication process,the proposed method WCA-BF+ASE has required only less storage space for variousfile sizes of 10 KB for 200,400 MB has taken only 22 KB,and 600 MB has required 35 KB,800 MB has consumed only 38 KB,1000 MB has taken 40 KB of storage spaces.
文摘The sensitive data stored in the public cloud by privileged users,such as corporate companies and government agencies are highly vulnerable in the hands of cloud providers and hackers.The proposed Virtual Cloud Storage Archi-tecture is primarily concerned with data integrity and confidentiality,as well as availability.To provide confidentiality and availability,thefile to be stored in cloud storage should be encrypted using an auto-generated key and then encoded into distinct chunks.Hashing the encoded chunks ensured thefile integrity,and a newly proposed Circular Shift Chunk Allocation technique was used to determine the order of chunk storage.Thefile could be retrieved by performing the opera-tions in reverse.Using the regenerating code,the model could regenerate the missing and corrupted chunks from the cloud.The proposed architecture adds an extra layer of security while maintaining a reasonable response time and sto-rage capacity.Experimental results analysis show that the proposed model has been tested with storage space and response time for storage and retrieval.The VCSA model consumes 1.5x(150%)storage space.It was found that total storage required for the VCSA model is very low when compared with 2x Replication and completely satisfies the CIA model.The response time VCSA model was tested with different sizedfiles starting from 2 to 16 MB.The response time for storing and retrieving a 2 MBfile is 4.96 and 3.77 s respectively,and for a 16 MBfile,the response times are 11.06 s for storage and 5.6 s for retrieval.
文摘本文描述了一个基于分层语块分析的统计翻译模型。该模型在形式上不仅符合同步上下文无关文法,而且融合了基于条件随机场的英文语块分析知识,因此基于分层语块分析的统计翻译模型做到了将句法翻译模型和短语翻译模型有效地结合。该系统的解码算法改进了线图分析的CKY算法,融入了线性的N-gram语言模型。目前,本文主要针对中文-英文的口语翻译进行了一系列实验,并以国际口语评测IWSLT(International Workshopon Spoken Language Translation)为标准,在2005年的评测测试集上,BLEU和NIST得分均比统计短语翻译系统有所提高。
