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A Lightweight ABE Security Protection Scheme in Cloud Environment Based on Attribute Weight
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作者 Lihong Guo Jie Yang Haitao Wu 《Computers, Materials & Continua》 SCIE EI 2023年第8期1929-1946,共18页
Attribute-based encryption(ABE)is a technique used to encrypt data,it has the flexibility of access control,high security,and resistance to collusion attacks,and especially it is used in cloud security protection.Howe... Attribute-based encryption(ABE)is a technique used to encrypt data,it has the flexibility of access control,high security,and resistance to collusion attacks,and especially it is used in cloud security protection.However,a large number of bilinear mappings are used in ABE,and the calculation of bilinear pairing is time-consuming.So there is the problem of low efficiency.On the other hand,the decryption key is not uniquely associated with personal identification information,if the decryption key is maliciously sold,ABE is unable to achieve accountability for the user.In practical applications,shared message requires hierarchical sharing in most cases,in this paper,we present a message security hierarchy ABE scheme for this scenario.Firstly,attributes were grouped and weighted according to the importance of attributes,and then an access structure based on a threshold tree was constructed according to attribute weight.This method saved the computing time for decryption while ensuring security and on-demand access to information for users.In addition,with the help of computing power in the cloud,two-step decryption was used to complete the access,which relieved the computing and storage burden on the client side.Finally,we simulated and tested the scheme based on CP-ABE,and selected different security levels to test its performance.The security proof and the experimental simulation result showthat the proposed scheme has high efficiency and good performance,and the solution implements hierarchical access to the shared message. 展开更多
关键词 attribute-based encryption cloud security message hierarchy attribute weight access control
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Attribute Weighted Naïve Bayes Classifier 被引量:1
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作者 Lee-Kien Foo Sook-Ling Chua Neveen Ibrahim 《Computers, Materials & Continua》 SCIE EI 2022年第4期1945-1957,共13页
The naïve Bayes classifier is one of the commonly used data mining methods for classification.Despite its simplicity,naïve Bayes is effective and computationally efficient.Although the strong attribute indep... The naïve Bayes classifier is one of the commonly used data mining methods for classification.Despite its simplicity,naïve Bayes is effective and computationally efficient.Although the strong attribute independence assumption in the naïve Bayes classifier makes it a tractable method for learning,this assumption may not hold in real-world applications.Many enhancements to the basic algorithm have been proposed in order to alleviate the violation of attribute independence assumption.While these methods improve the classification performance,they do not necessarily retain the mathematical structure of the naïve Bayes model and some at the expense of computational time.One approach to reduce the naïvetéof the classifier is to incorporate attribute weights in the conditional probability.In this paper,we proposed a method to incorporate attribute weights to naïve Bayes.To evaluate the performance of our method,we used the public benchmark datasets.We compared our method with the standard naïve Bayes and baseline attribute weighting methods.Experimental results show that our method to incorporate attribute weights improves the classification performance compared to both standard naïve Bayes and baseline attribute weighting methods in terms of classification accuracy and F1,especially when the independence assumption is strongly violated,which was validated using the Chi-square test of independence. 展开更多
关键词 attribute weighting naïve Bayes Kullback-Leibler information gain CLASSIFICATION
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WEIGHTED ALGORITHM FOR FINGERPRINTING RELATIONAL DATABASES 被引量:1
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作者 崔新春 秦小麟 +1 位作者 管致锦 束瑜 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2008年第2期148-154,共7页
The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher wei... The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher weights are assigned to more significant attributes, so important attributes are more frequently fingerprinted than other ones. Finally, the robustness of the proposed algorithm, such as performance against collusion attacks, is analyzed. Experimental results prove the superiority of the algorithm. 展开更多
关键词 digital fingerprinting relational database systems copyright protection attribute weight traitor tracing
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An Integrated FCEM-AHP Approach for Borrower’s Satisfaction and Perception Analysis of Microfinance Institution 被引量:1
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作者 Munawar Hassan Shafqat Iqbal +2 位作者 Harish Garg Shahbaz Gul Hassan Yunxian Yan 《Computer Modeling in Engineering & Sciences》 SCIE EI 2023年第1期559-584,共26页
Themain objective of this paper is to present an integrated approach to evaluate the level of satisfaction of borrowers with the products and services of microfinance institutions(MFI)at different criterion levels.For... Themain objective of this paper is to present an integrated approach to evaluate the level of satisfaction of borrowers with the products and services of microfinance institutions(MFI)at different criterion levels.For this,the study adopts the concept of FCEM(Fuzzy Comprehensive EvaluationMethod)in concurrence with the AHP(Analytical Hierarchy Process).In our day-to-day situation,the researchers have made many efforts to assess the impact of Microfinance on poverty reduction,but borrowers’satisfaction is always overlooked.Since the multiple factors impact the borrower’s satisfaction,each factor is made of different items.Thus,as the factors items increase,many uncertainties are created,and hence this will make the decisionmaking unsmooth or imprecise.To describe this,the FCEM method deals with the vagueness in the collection information phase.However,the AHP has been utilized to determine the objective weights of each factor.The presented integrated framework has been illustrated with a case study and presented their results.The study’s managerial benefit is also reported to address the situation. 展开更多
关键词 AHP attribute weights borrower satisfaction FCEM MICROFINANCE
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Study on Chinese Webpage Keyword Extraction based on Multiple Index Factors
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《International English Education Research》 2013年第12期127-129,共3页
Webpage keyword extraction is very important for automatically extracting webpage summary, retrieval, automatic question answering, and character relation extraction, etc. In this paper, the environment vector of word... Webpage keyword extraction is very important for automatically extracting webpage summary, retrieval, automatic question answering, and character relation extraction, etc. In this paper, the environment vector of words is constructed with lexical chain, words context, word frequency, and webpage attribute weights according to the keywords characteristics. Thus, the multi-factor table of words is constructed, and then the keyword extraction issue is divided into two types according to the multi-factor table of words: keyword and non-keyword. Then, words are classified again with the support vector machine (SVM), and this method can extract the keywords of unregistered words and eliminate the semantic ambiguities. Experimental results show that this method is with higher precision ratio and recall ratio compared with the simple ff/idf algorithm. 展开更多
关键词 Lexical Chain CONTEXT attribute weights of Webpage Support Vector Machine (SVM) Eliminate Semantic Ambiguities
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Pattern discovery of long non-coding RNAs associated with the herbal treatments in breast and prostate cancers
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作者 Elham Dalalbashi Esfahani Esmaeil Ebrahimie +1 位作者 Ali Niazi Manijeh Mohammadi Dehcheshmeh 《Quantitative Biology》 CSCD 2023年第3期343-358,共16页
Background:Accumulating evidence shows that long non-coding RNAs(lncRNAs)play critical roles in cancer progression.The possible association between lncRNAs and herbal medicine is yet to be known.This study aims to ide... Background:Accumulating evidence shows that long non-coding RNAs(lncRNAs)play critical roles in cancer progression.The possible association between lncRNAs and herbal medicine is yet to be known.This study aims to identify medicinal herbs associated with lncRNAs by RNA-seq data for breast and prostate cancer.Methods:To develop the optimal approach for identifying cancer-related lncRNAs,we implemented two steps:(1)applying protein–protein interaction(PPI),Gene Ontology(GO),and pathway analyses,and(2)applying attribute weighting and finding the efficient classification model of the machine learning approach.Results:In the first step,GO terms and pathway analyses on differential co-expressed mRNAs revealed that lncRNAs were widely co-expressed with metabolic process genes.We identified two hub lncRNA-mRNA networks that implicate lncRNAs associated with breast and prostate cancer.In the second step,we implemented various machine learning-based prediction systems(Decision Tree,Random Forest,Deep Learning,and Gradient-Boosted Tree)on the non-transformed and Z-standardized differential co-expressed lncRNAs.Based on five-fold cross-validation,we obtained high accuracy(91.11%),high sensitivity(88.33%),and high specificity(93.33%)in Deep Learning which reinforces the biomarker power of identified lncRNAs in this study.As data originally came from different cell lines at different durations of herbal treatment intervention,we applied seven attribute weighting algorithms to check the effects of variables on identifying lncRNAs.Attribute weighting results showed that the cell line and time had little or no effect on the selected lncRNAs list.Besides,we identified one known lncRNAs,downregulated RNA in cancer(DRAIC),as an essential feature.Conclusions:This study will provide further insights to investigate the potential therapeutic and prognostic targets for prostate cancer(PC)and breast cancer(BC)in common. 展开更多
关键词 RNA-SEQ lncRNA CANCER CO-EXPRESSION machine learning attribute weighting
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Analysis of Classical Encryption Techniques in Cloud Computing 被引量:1
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作者 Muhammad Yasir Shabir Asif Iqbal +1 位作者 Zahid Mahmood Ata Ullah Ghafoor 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2016年第1期102-113,共12页
Cloud computing has become a significant computing model in the IT industry. In this emerging model,computing resources such as software, hardware, networking, and storage can be accessed anywhere in the world on a pa... Cloud computing has become a significant computing model in the IT industry. In this emerging model,computing resources such as software, hardware, networking, and storage can be accessed anywhere in the world on a pay-per-use basis. However, storing sensitive data on un-trusted servers is a challenging issue for this model. To guarantee confidentiality and proper access control of outsourced sensitive data, classical encryption techniques are used. However, such access control schemes are not feasible in cloud computing because of their lack of flexibility, scalability, and fine-grained access control. Instead, Attribute-Based Encryption(ABE) techniques are used in the cloud. This paper extensively surveys all ABE schemes and creates a comparison table for the key criteria for these schemes in cloud applications. 展开更多
关键词 cloud computing access control fine-grained access weighted attribute
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Bridging Real World Semantics to Model World Semantics for Taxonomy Based Knowledge Representation System
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作者 Ju-HumKwon Chee-YangSong +1 位作者 Chang-JooMoon Doo-KwonBaik 《Journal of Computer Science & Technology》 SCIE EI CSCD 2005年第3期296-308,共13页
As a mean to map ontology concepts, a similarity technique is employed.Especially a context dependent concept mapping is tackled, which needs contextual information fromknowledge taxonomy. Context-based semantic simil... As a mean to map ontology concepts, a similarity technique is employed.Especially a context dependent concept mapping is tackled, which needs contextual information fromknowledge taxonomy. Context-based semantic similarity differs from the real world similarity in thatit requires contextual information to calculate similarity. The notion of semantic coupling isintroduced to derive similarity for a taxonomy-based system. The semantic coupling shows the degreeof semantic cohesiveness for a group of concepts toward a given context. In order to calculate thesemantic coupling effectively, the edge counting method is revisited for measuring basic semanticsimilarity by considering the weighting attributes from where they affect an edge''s strength. Theattributes of scaling depth effect, semantic relation type, and virtual connection for the edgecounting are considered. Furthermore, how the proposed edge counting method could be well adaptedfor calculating context-based similarity is showed. Thorough experimental results are provided forboth edge counting and context-based similarity. The results of proposed edge counting wereencouraging compared with other combined approaches, and the context-based similarity also showedunderstandable results. The novel contributions of this paper come from two aspects. First, thesimilarity is increased to the viable level for edge counting. Second, a mechanism is provided toderive a context-based similarity in taxonomy-based system, which has emerged as a hot issue in theliterature such as Semantic Web, MDR, and other ontology-mapping environments. 展开更多
关键词 semantic similarity context-based similarity edge counting semanticcoupling weighting attributes WORDNET
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