Keyword Index Research Articles

Efficient Boolean Keywords Search over Encrypted Cloud Data in Public Key Setting

Searchable public key encryption- (SPE-) supporting keyword search plays an important role in cloud computing for data confidentiality. The current SPE scheme mainly supports conjunctive or disjunctive keywords search which belongs to very basic query operations. In this paper, we propose an efficient and secure SPE scheme that supports Boolean keywords search, which is more advanced than the conjunctive and disjunctive keywords search. We first develop a keyword conversion method, which can change the index and Boolean keywords query into a group of vectors. Then, through applying a technique so-called dual pairing vector space to encrypt the obtained vectors, we propose a concrete scheme proven to be secure under chosen keyword attack. Finally, we put forward a detailed theoretical and experimental analysis to demonstrate the efficiency of our scheme.

빅데이터를 활용한 영화흥행 요인 분석 : 영화 <기생충>의 SNS 활용지수와 토픽키워드 중심으로

빠르게 변화하고 있는 4차 산업 시대에 빅데이터는 다양한 분야에 활용되고 있다. 최근 문화예술콘텐츠 전반에도 빅데이터의 활용은 급속도로 적용되고 있고, 그중에서도 영화는 자본이 많이 드는 예술장르로서 빅데이터의 활용은 매우 유용한 분석 수단이다.<BR> 본 연구는 2019년 제72회 칸 영화제의 황금종려상과 아카데미 시상식에서 4관왕(작품상, 감독상, 각본상, 외국어 영화상)을 차지하며 한국영화의 가치를 보여준 영화 <기생충>을 대상으로 빅데이터 분석기법을 적용하여 실시하였다. 이렇게 분석된 값은 데이터의 주기별 변화량과 감성의 값을 부여하는 오피니언 마이닝을 통해 영화 흥행을 예측하고, 페이스북(Facebook), 트위터(Twitter) 등 SNS의 활용지수와 토픽 키워드를 추출하여 관객들의 관심을 반영하는 영화적 요인들이 무엇인지를 살펴보았다. 이처럼 빅데이터를 활용한 영화흥행 요인분석으로 모델 구축 및 모형 개발로 흥행예측이 가능해지면 영화제작 과정의 효율성을 극대화하면서 제작비용과 영화실패에 따른 리스크를 최소화 할 것이다.

Keyword Indexing And Searching Tool (KIST): A Tool to Assist the Forensics Analysis of WhatsApp Chat

Digital forensics is a field that concerned with finding and presenting evidence sourced from digital devices, such as computers and mobile phones. Most of the forensic analysis software is proprietary, and eventually, specialized analysis software is developed in both the private and public sectors. This paper presents an alternative of forensic analysis tools for digital forensics, which specifically to analyze evidence through keyword indexing and searching. Keyword Indexing and Searching Tool (KIST) is proposed to analyze evidence of interest from WhatsApp chat text files using keyword searching techniques and based on incident types. The tool was developed by adopting the Prototyping model as its methodology. KIST includes modules such as add, edit, remove, display the indexed files, and to add WhatsApp chat text files. Subsequently, the tool is tested using functionality testing and user testing. Functionality testing shows all key functions are working as intended, while users testing indicates the majority of respondents are agree that the tool is able to index and search keyword and display forensic analysis results.

Editorial Policy

Editorial Policy

Key-Policy Attribute-Based Encryption With Keyword Search in Virtualized Environments

Cloud computing is a model for convenient, on-demand network access to virtualized environments of configurable computing resources. It is challenging to search data encrypted and stored in cloud storage servers. Searchable encryption enables data users to search on ciphertext without leaking any information about keywords and the plaintext of the data. Currently, a number of searchable encryption schemes have been proposed, but most of them provide unlimited search privileges to data users, which is not desirable in certain scenarios. In this paper, we propose a new construction of searchable encryption with fine-grained access control by using key-policy attribute-based cryptography to generate trapdoors to support AND, OR and threshold gates. The main idea is that the data owner encrypts the index keywords according to the specified access policy. The data user can generate a trapdoor to search on data, if and only if the attributes of the data user satisfy the access policy. We provide formal security proofs for the scheme, including the indistinguishability of ciphertexts and the indistinguishability of trapdoors, which are used to resist the chosen keyword attack and the keyword guessing attack of external adversaries. Comprehensive security analysis and implementation results show that the proposed scheme is provably secure and feasible in real-world applications.

A synthesis method for path generation of a planar five-bar mechanism based on dynamic self-adaptive atlas database

A method for the path synthesis of a planar five-bar mechanism based on wavelet analysis theory is proposed in this paper. Wavelet transform analysis is used to extract wavelet characteristic parameters(WCPs) from the basic dimensional types(BDTs) database. Combined the numerical atlas method with multidimensional search tree, a four dimensions search tree with a depth of five is obtained, in which numbers of leaf nodes are 4,096, and each node stores 59,787 groups of BDTs database numbers. Meanwhile, an index keyword database is established. By comparing the WCPs of a prescribed curve with index keywords, the leaf node where the desired mechanism is located is found. The WCPs of the BDTs in the leaf node are extracted, and a dynamic self-adaptive atlas database is established. Based on the design requirements, the desired mechanism can be obtained by fuzzy identification. Then, a mathematical model is established for calculating the actual sizes of the desired mechanism. The arbitrary design interval path synthesis of a five-bar mechanism is realized. Two examples are presented to demonstrate the veracity and practicality of the method proposed.

Identification of COVID-19 Outbreak Signals Prior to the Traditional Disease Surveillance System

Background: New coronavirus cases and deaths are continuing to pop up worldwide. Early identifying the emergence of a novel infectious disease outbreak is of great value for a timely response. Methods: We performed a comparative study to discuss the feasibility of early warning of the outbreak of novel coronavirus (COVID-19) based on the influenza surveillance data and internet search index of keywords in order to evaluate the early warning capability and timelines of the alert signals in comparison with the traditional case reporting system and official response in China. Findings: Influenza cases notified in 2019 was significantly higher in comparison to previous years in China. An early spike of influenza was observed in 2019 winter, with a fast-growing period from November to December, suggesting that the COVID-19 cases may occur during October and November or earlier. There was a surge in searching for information related to “pneumonia” and “SARS” on 31 December 2019. However, according to the traditional official surveillance system, the risk of the potential epidemic was not taken seriously since the first group of unexplained pneumonia cases reported in Wuhan on 29 December, 2019, till 20 January, 2020. Both the unusual increase of influenza and the peak of internet search for key terms have shown earlier signals of the outbreak of COVID-19. Interpretation: The traditional disease monitoring system is effective to detect the outbreak of common infectious diseases, but it is insufficient for the discovery of novel diseases. Monitoring abnormal spike of influenza-like illness and identifying online search peak of key terms can provide early signals of a novel disease outbreak. Funding Statement: This study was funded by the National Natural Science Foundation of China (81973103), National Key R&D Program of China (2017YFC0907000), and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD). Declaration of Interests: The authors declare no conflict of interest. Ethics Approval Statement: This study was approved by the ethics committee of Nanjing Medical University.

Keyword index

Annals of Applied BiologyVolume 176, Issue 3 p. 371-372 KEYWORD INDEX Keyword index First published: 18 May 2020 https://doi.org/10.1111/aab.kwindex_176AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume176, Issue3May 2020Pages 371-372 RelatedInformation

Pengaruh Risiko Bisnis, Profitabilitas dan Pertumbuhan Aset terhadap Struktur Modal Perusahaan yang Terdaftar di Jakarta Islamic Index

Purpose - This study aims to determine the effect of business risk, profitability, and asset growth on the capital structure of companies listed on the Jakarta Islamic Index.Methodology - This research is classified as causative research. The population in this study were all companies listed on the Jakarta Islamic Index in 2014-2018. The sample in this study was determined by purposive sampling based on the criteria of companies listed in the Jakarta Islamic Index, companies that are consecutively ranked in the Jakarta Islamic Index during the 2014-2018. The samples in this study were 70. The type of data used is secondary data from the website www.idx.co.id. The analytical method used is multiple regression analysis using the SPSS program.Finding - The result of this study indicate (1) business risk has no significant negative effect on capital structure in companies listed on the Jakarta Islamic Index (2) profitability has a significant positive effect on capital structure in companies listed on the Jakarta Islamic Index (3) asset growth has a significant positive effect on capital structure in companies listed on the Jakarta Islamic Index Keywords: Capital Structure, Business Risk, Profitability, and Asset Growth

Appendix JSTMC Vol.20 No.2 December 2019 : Author Index &amp; Keyword Index

Appendix JSTMC Vol.20 No.2 December 2019 : Author Index &amp; Keyword Index

Appendix JSTMC Vol.20 No.1 June 2019 : Author Index &amp; Keyword Index

Appendix JSTMC Vol.20 No.1 June 2019 : Author Index &amp; Keyword Index

VPAMS: Verifiable and practical attribute-based multi-keyword search over encrypted cloud data

Abstract With fast development of cloud storage, people increasingly outsource their files to the cloud server. To protect the confidentiality of outsourced files, files often are encrypted before outsourced. However, the accurate location and search on encrypted files will be greatly limited. This paper mainly considers how to realize an accurate multi-keyword fine-grained search on the encrypted files. Firstly, we use multiple keywords and an improved k-nearest neighbor (k-NN) technology to improve the search accuracy. Secondly, our scheme can protect the privacy of the file keyword indexes and the search queries and further preserve the privacy of outsourced files and users. Thirdly, unlike other existing multi-keyword search schemes without considering the verification and decryption of search results, the data users in our scheme not only can check whether the returned files contain multiple queried keywords, but also can realize the authorized decryption of the search files by using attribute-based encryption. Finally, performance evaluations show the time costs of our search algorithm is a constant value and independent of the number of user attributes. Therefore, our scheme is more efficient and practical.

An Efficient Attribute-Based Multi-Keyword Search Scheme in Encrypted Keyword Generation

With the growing popularity of cloud computing in recent years, data owners (DOs) now prefer to outsource their data to cloud servers and allow the specific data users (DUs) to retrieve the data. Searchable encryption is an important tool to provide secure search over the encrypted cloud data without infringing data confidentiality and data privacy. In this work, we consider a secure search service providing fine-grained and search functionality, called attribute-based multiple keyword search (ABMKS), which can be seen as an extension of searchable encryption. In the existing ABMKS schemes, the computation operations in the encrypted keyword index generation are time-consuming modular exponentiation, and the number of which is linearly growing with the factor $m$ . Here $m$ is the number of keywords embedded in a file. To reduce the computation overhead, in this paper, we propose an ABMKS with only multiplication operations in encrypted keyword index generation. As a result, the computation cost of the encrypted keyword index generation is more efficient than the existing schemes. In addition, the encrypted keyword indexes are aggregated into one item, which is regardless of the number of underlying keywords in a file data. Finally, the security and the performance analysis demonstrate that our scheme is both efficient and secure.

Authorized Keyword Searches on Public Key Encrypted Data With Time Controlled Keyword Privacy

Recently, more and more data have been stored in the cloud with keyword indices so that the data users can make search over the databases. In some of these database applications, the query frequency analysis of keywords is quite important to the optimization of the databases and it is easy to be implemented when the data are not encrypted. However, with the growing demands of data privacy, it is desired that the data should be encrypted before uploaded to the cloud. Searchable encryption has been proposed which enables users to make keyword search over the encrypted data with keyword privacy. In a secure searchable encryption scheme, it is required that the keyword in each query should not be revealed. So it becomes challenging to analyze the query frequency of keywords in an encrypted database which has the pressing need of optimization. In this paper, we first consider this problem and present an efficient solution to it which enables the query frequency analysis of keywords without destroying the privacy of the encrypted data and the identity privacy of data users. We also simulate our solution and show that it is practical to the real applications.

ACNP 58th Annual Meeting: Keyword Index

ACNP 58th Annual Meeting: Keyword Index

Keyword Index

The Kaohsiung Journal of Medical SciencesVolume 35, Issue 12 p. VI-VIII INDEXOpen Access Keyword Index First published: 14 December 2019 https://doi.org/10.1002/kjm2.12170AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume35, Issue12December 2019Pages VI-VIII RelatedInformation

On the Security of Privacy-Preserving Attribute-Based Keyword Search in Shared Multi-owner Setting

Recently in the IEEE Transactions on Dependable and Secure Computing (doi: 10.1109/TDSC.2019.28976752019), Miao et al. proposed a novel construction of Privacy-Preserving Attribute-Based Keyword Search in Shared Multi-owner Setting (ABKS-SM), which can delegate keyword search tasks to cloud server provider (CSP) without revealing any useful information. Although the authors claimed that the offline keyword guessing attacks can be resisted in ABKS-SM scheme, we show that this scheme indeed suffers from four types of offline keyword guessing attacks and hence fails to gain the claimed security property, which is an important goal to be achieved in searchable encryption schemes. Specifically, given the concrete attacks, we demonstrate that the underlying keyword information can be extracted from both encrypted keyword indexes and trapdoors by any malicious user and any adversarial CSP. We hope that the similar security vulnerabilities could be avoided in the future design of related searchable encryption schemes.

Keyword Index to Volume 44, 2019

Keyword Index to Volume 44, 2019

Author and Keyword Indexes for Volume 50

Author and Keyword Indexes for Volume 50

Unravelling the Nexus between neuroscience and leadership research

PurposeThe collaboration of the field of neuroscience and leadership has invoked a general curiosity in the area of leadership studies. The discipline is giving copious amounts of inputs for the smooth functioning of the organization. Such collaborated studies attempt to establish improvements in the leadership research with the aid of thinking, feeling and knowing dimensions. Though generic understanding is available, the studies done on the neuro-leadership collaborations are far and few. The purpose of this paper mainly is to attempt to decipher the level of understanding the scientific world has on the inter-disciplinary interactions between neuroscience and leadership studies.Design/methodology/approachA biblio-morphological analysis is carried out. This integrated methodology is being introduced for the first time in the area of a literature review. The topic of interest is a novel one and being spread across many disciplines warrants such a comprehensive approach. The bibliometric analysis is carried out with the help of VOSviewer software.FindingsThe different parameters analyzed in this analysis are: mapping based on text data, index keyword, main authors who are the pioneers in the area, countries which are the leaders in the field of neuroscience and leadership studies. Such an analysis broadly outlines the present status of the research on the topic. Morphological analysis is executed by dissecting the topic into various dimensions and sub-options. These dimensions are then cross-matched in a matrix, known as the cross-consistency matrix. This matrix reflects the 174 research gaps that exist in this particular area.Originality/valueThe biggest contribution of this paper would be to underline the present status of the literature on neuroscience and leadership research and to develop a reference for future opportunities. This study attempts to make this document a vade mecum for both the industry and the academia in the area of neuroscience and leadership research.