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A blockchain is designed to establish consistent and reliable agreements in an untrusted and decentralized environment. In addition, the blockchain enables transaction processing and the creation of smart contracts. It empowers end users to execute contracts without any intermediate entities. However, there are some issues when it comes to retrieving information, such as the state and history of smart contracts and regular transactions in the blockchain. For example, in a smart contract, user-defined data structures can be used to recall the state of the smart contract for a range query, which can decrease the general performance. In addition, an external database can be required to retrieve regular transactions for range queries, which increases management costs. To achieve this, we propose a new scheme that enables SQL query operations to retrieve a smart contract and regular transaction information within the blockchain system. To achieve this, we combine an embedded relational database with an Ethereum-based blockchain system to provide the SQL query. It enables range queries on smart contracts without requiring user-defined data structures and decreases management costs for regular transactions without any external database. We implement the proposed blockchain system on quorum, which is an Ethereum-based blockchain system. Also, we evaluate the proposed system using a synthetic benchmark. The performance of retrieving smart contract data is improved by up to approximately 22×, with low memory usage compared with the existing system. Moreover, the proposed system demonstrates a similar search performance to the existing system, even when considering external databases in regular transactions. [ABSTRACT FROM AUTHOR]

Dalam pengoperasian database MaraiaDB diperlukan aplikasi berupa server localhost yang memiliki response waktu untuk menjalankan sebuah query agar dapat mendapatkan waktu yang efisiensi. Pada penelitian ini mengukur perfoma query dalam bentuk SELECT pada database MariaDB yang sudah di install pada komputer atau laptop dengan menggunakan aplikasi yang bernama Xammp dengan jumlah record data kurang lebih sebanyak 12.000 data, tapi pada penelitian ini hanya memakai sekitar 5000 data. Data tersebut nantinya akan dilakukan optimasi query dan indexing. Permasalahan yang terjadi adalah lamanya proses pengambilan data yang membutuhkan waktu sehingga membutuhkan suatu cara agar dapat mempercepat proses pengambilan data. Metode optimasi database yang difokuskan pada pengujian ini adalah dengan melakukan perbandingan dari berbagai efektivitas sub query serta penggunaan indexing pada tabel. Pada Query yang diuji adalah fungsi yang bernama LEFT JOIN, WHERE, ON, GROUP BY, ORDER BY dan DML (Data Manipulation Language), yaitu QUERY SELECT yang akan di lakukan pada aplikasi Xammp. Pada penelitian ini hasil yang di harapkan berupa pengambilan data yang akan menjadi lebih cepat atau efisien untuk meningkatkan kinerja pada database setelah melakukan Optimasi SQL Query dan Table Indexing.

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Information technology (IT) service providers are nowadays moving toward cloud computing. Software-as-a-service (SaaS) refers to cloud service-oriented web applications. As a result of computation outsourcing, a customer (tenant) can subscribe to a self-service SaaS and use it on a pay-per-use basis. To reduce resource costs, a single instance of SaaS serves multiple tenants (multi-tenancy). However, outsourcing and multi-tenancy bring about new security issues. Indeed, tenants lose control over the source code, databases and infrastructure and cannot deploy their own intrusion detection system (IDS). In this context, the provider must not only integrate their preferred IDS into a public cloud, but also protect the tenants according to their individual security requirements. We put forth a multi-tenant intrusion detection framework as a service for SaaS (MTIDaaS) to allow the provider to undertake such integration. Our MTIDaaS has been integrated and tested in a real public cloud environment. It provides security-as-a-service (SecaaS) for both provider and tenant with high levels of portability, flexibility and cost-effectiveness. The experimental results demonstrate that our MTIDaaS offers easy integration of IDS with little virtualization overhead and insignificant impact on HTTP response time. [ABSTRACT FROM AUTHOR]

Data exploration—the problem of extracting knowledge from database even if we do not know exactly what we are looking for —is important for data discovery and analysis. However, precisely specifying SQL queries is not always practical, such as "finding and ranking off-road cars based on a combination of Price, Make, Model, Age, Mileage, etc"—not only due to the query complexity (e.g.,the queries may have many if-then-else, and, or and not logic), but also because the user typically does not have the knowledge of all data instances (and their variants). We propose DExPlorer, a system for interactive data exploration. From the user perspective, we propose a simple and user-friendly interface, which allows to: (1) confirm whether a tuple is desired or not, and (2) decide whether a tuple is more preferred than another. Behind the scenes, we jointly use multiple ML models to learn from the above two types of user feedback. Moreover, in order to effectively involve human-in-the-loop, we need to select a set of tuples for each user interaction so as to solicit feedback. Therefore, we devise question selection algorithms, which consider not only the estimated benefit of each tuple, but also the possible partial orders between any two suggested tuples. Experiments on real-world datasets show that DExPlorer outperforms existing approaches in effectiveness. [ABSTRACT FROM AUTHOR]

Spurred by the development of cloud computing, there has been considerable recent interest in the Database-as-a-Service (DaaS) paradigm. Users lacking in expertise or computational resources can outsource their data and database management needs to a third-party service provider. Outsourcing, however, raises an important issue of result integrity: how can the client verify with lightweight overhead that the query results returned by the service provider are correct (i.e., the same as the results of query execution locally)? This survey focuses on categorizing and reviewing the progress on the current approaches for result integrity of SQL query evaluation in the DaaS model. The survey also includes some potential future research directions for result integrity verification of the outsourced computations. [ABSTRACT FROM AUTHOR]

Subject of Research.The paper considers common natural language processing stages such as morphological, syntactic and semantic analysis. We describe connections between query parts, semantic model and internal database representation. Method. A method is proposed for the database semantic model application as a part of the natural language user database interface. There is a description of the semantic model data transforms to intermediate Q-representation of the user query. The next step is transforming of Q-representation to database SQL query based on substitution to predefined query template. Main Results. We give an account of the semantic model application as a part of natural language user interface. An example is provided of the transformation of both simple and nested natural language user queries to the database SQL query. The paper presents experimental research results of the proposed method of the semantic model application as a part of the natural language user database interface. Practical Relevance. Implementation of the proposed approach gives the possibility to resolve the problem of extracting information from the database based on user’s natural language query. This method also improves the process of resolving the ambiguity during natural language processing. The presence of information about internal database structure makes it possible to create more accurate database SQL query.

Although scientific literature studies different aspects of SQL query optimization the major part of researches is limited to the theoretical analysis of problems. There is a lack of researches that ground the effectiveness of SQL query optimization methods on the results of experimental testing. In light of this the aim of the current research is to assess the importance of SQL code optimization, data base indexes and structure in the creation of optimized SQL queries by means of experimental testing. The results of this research are important for the programmers of information systems, databases and other IT specialist who create information systems and analyze the data of databases. The results of experimental research can be used in high schools teaching databases. Research object is SQL query optimization. Research objective is to perform the research of SQL query optimization optimizing SQL code, using data base indexes and denormalizing data base structure. Research tasks: To assess the impact of SQL code on the effectiveness of SQL query. To ascertain how data base indexes influence the duration of SQL query execution. To assess the impact of data base denormalization on the effectiveness of SQL queries. Research methods: the impact of SQL code, data base indexes and data base denormalization on the effectiveness of SQL queries was assessed my means of experimental testing. The experimental testing was implemented in Oracle XE data base management system conducting tests in various in size databases, indexing them and denormalizing. The conducted research is important both in theoretical and practical aspects. Research results are important for data base programmers and other IT specialists who execute SQL queries. The results of the conducted research can be integrated into the data base subject teaching in higher schools grounding the importance of SQL query optimization and defining good practice of SQL code writing. The presented research method can be also used assessing the effectiveness of queries in NoSQL databases. Conclusions: During the assessment of the impact of SQL code on the effectiveness of query it was established that properly written SQL code reduces the duration SQL query execution by 85,0 percent. The duration of query execution is negatively influenced by internal queries, phrase HAVING and use of operator The designation of query field in SELECT phrase can reduce the duration of query execution by 27,0 percent. The conducted experimental research showed that the indexing of query fields used in calculations has negative impact on the duration of query execution. The indexing of query fields that form selection criteria is effective only when selection query returns less than 10,0 percent of data base records. The conducted experimental research showed that the denormalization of data base has positive impact on the effectiveness of SQL queries. Denormalizing data base on purpose to avoid connections in SQL query use it is possible to reduce the time of query execution by 89,0 percent.

With the advent of database-as-a-service (DAAS) and cloud computing, more and more data owners are motivated to outsource their data to cloud database in consideration of convenience and cost. However, it has become a challenging work to provide security to database as service model in cloud computing, because adversaries may try to gain access to sensitive data, and curious or malicious administrators may capture and leak data. In order to realize privacy preservation, sensitive data should be encrypted before outsourcing. In this paper, we present a secure and practical system over encrypted cloud data, called QSDB (queryable and secure database), which simultaneously supports SQL query operations. The proposed system can store and process the floating point numbers without compromising the security of data. To balance tradeoff between data privacy protection and query processing efficiency, QSDB utilizes three different encryption models to encrypt data. Our strategy is to process as much queries as possible at the cloud server. Encryption of queries and decryption of encrypted queries results are performed at client. Experiments on the real-world data sets were conducted to demonstrate the efficiency and practicality of the proposed system. [ABSTRACT FROM AUTHOR]

Background: Korian is a private group specializing in medical accommodations for elderly and dependent people. A professional data warehouse (DWH) established in 2010 hosts all of the residents' data. Inside this information system (IS), clinical narratives (CNs) were used only by medical staff as a residents' care linking tool. The objective of this study was to show that, through qualitative and quantitative textual analysis of a relatively small physiotherapy and well-defined CN sample, it was possible to build a physiotherapy corpus and, through this process, generate a new body of knowledge by adding relevant information to describe the residents' care and lives.Methods: Meaningful words were extracted through Standard Query Language (SQL) with the LIKE function and wildcards to perform pattern matching, followed by text mining and a word cloud using R® packages. Another step involved principal components and multiple correspondence analyses, plus clustering on the same residents' sample as well as on other health data using a health model measuring the residents' care level needs.Results: By combining these techniques, physiotherapy treatments could be characterized by a list of constructed keywords, and the residents' health characteristics were built. Feeding defects or health outlier groups could be detected, physiotherapy residents' data and their health data were matched, and differences in health situations showed qualitative and quantitative differences in physiotherapy narratives.Conclusions: This textual experiment using a textual process in two stages showed that text mining and data mining techniques provide convenient tools to improve residents' health and quality of care by adding new, simple, useable data to the electronic health record (EHR). When used with a normalized physiotherapy problem list, text mining through information extraction (IE), named entity recognition (NER) and data mining (DM) can provide a real advantage to describe health care, adding new medical material and helping to integrate the EHR system into the health staff work environment. [ABSTRACT FROM AUTHOR]

We study the possibility of obtaining functional dependencies from the scheme of the existing database, as well as the data contained in it. Statistical methods for finding dependencies between data were used to generate probability dependencies. Software implementation of the developed algorithm for generating dependencies provides connection to various data providers. Application testing showed that the correct results can be obtained with a sufficiently large amount of data in the source. [ABSTRACT FROM AUTHOR]

This paper explores the issue of group integrity of tuple subsets regarding corporate integrity constraints in relational databases. A solution may be found by applying the finite-state machine theory to guarantee group integrity of data. We present a practical guide to coding such an automaton. After creating SQL queries to manipulate data and control its integrity for real data domains, we study the issue of query performance, determine the level of transaction isolation, and generate query plans.

Abstract: Security and privacy of database-driven web applications are extremely multifaceted against web intruders. One of the most dangerous cyber attacks is the SQL-injection attack, which simply creates huge loss to commercial vendors. Research deliberates to provide SQL-injection free (SQL-IF) secure algorithm to detect and prevent SQL-injection attacks (SQLIAs). In this paper, we have re-addressed several detection methods to conflict against the proposed SQL-IF secure algorithm. The generated algorithm has been integrated into the runtime environment while the implementation has been done through Java. The algorithm describes the method that how we follow the procedures for preventing SQL-injection attacks. We presented the SQL-IF secure algorithm and logic of the generated code. Comparison of similar types of attack along with different features is performed. The empirical results and its evaluation prove that the algorithm works efficiently to detect the SQLIAs. [Copyright &y& Elsevier]

Abstract: Small and Medium-sized Enterprises (SMEs) in the process of wage entry, calculation, the total number are needed to be done manually in the past, the data volume is quite large, processing speed is low, and it is easy to make error, which is resulting in low efficiency. The main purpose of writing this paper is to present the basis of salary management system, establish a scientific database, the computer payroll system, using the computer instead of a lot of past manual work in order to reduce duplication of staff labor, it will improve working efficiency.This system combines the actual needs of SMEs, through in-depth study and practice of the C/S mode, PowerBuilder10.0 development tools, databases and SQL language, Completed a payroll system needs analysis, database design, application design and development work. Wages, departments, units and personnel database file are included in this system, and have data management, department management, personnel management and other functions, through the control and management of the database query, add, delete, modify, and other functions can be realized. This system is reasonable design, a more complete function, stable operation has been tested to meet the basic needs of the work. [Copyright &y& Elsevier]

Abstract: SQL injection or SQL insertion attack is a code injection technique that exploits a security vulnerability occurring in the database layer of an application and a service. This is most often found within web pages with dynamic content. This paper proposes a very simple and effective detection method for SQL injection attacks. The method removes the value of an SQL query attribute of web pages when parameters are submitted and then compares it with a predetermined one. This method uses combined static and dynamic analysis. The experiments show that the proposed method is very effective and simple than any other methods. [Copyright &y& Elsevier]