A key function of a software system is its ability to facilitate the manipulation of data, which is often implemented using a flavour of the Structured Query Language (SQL). To develop the data ...operations of software (i.e, creating, retrieving, updating, and deleting data), developers are required to excel in writing and combining both SQL and application code. The problem is that writing SQL code in itself is already challenging (e.g., SQL anti-patterns are commonplace) and combining SQL with application code (i.e., for SQL development tasks) is even more demanding. Meanwhile, we have little empirical understanding regarding the characteristics of SQL development tasks. Do SQL development tasks typically need more code changes? Do they typically have a longer time-to-completion? Answers to such questions would prepare the community for the potential challenges associated with such tasks. Our results obtained from 20 Apache projects reveal that SQL development tasks have a significantly longer time-to-completion than SQL-unrelated tasks and require significantly more code changes. Through our qualitative analyses, we observe that SQL development tasks require more spread out changes, effort in reviews and documentation. Our results also corroborate previous research highlighting the prevalence of SQL anti-patterns. The software engineering community should make provision for the peculiarities of SQL coding, in the delivery of safe and secure interactive software.
Computers are now involved in many economic transactions and can capture data associated with these transactions, which can then be manipulated and analyzed. Conventional statistical and econometric ...techniques such as regression often work well, but there are issues unique to big datasets that may require different tools. First, the sheer size of the data involved may require more powerful data manipulation tools. Second, we may have more potential predictors than appropriate for estimation, so we need to do some kind of variable selection. Third, large datasets may allow for more flexible relationships than simple linear models. Machine learning techniques such as decision trees, support vector machines, neural nets, deep learning, and so on may allow for more effective ways to model complex relationships. In this essay, I will describe a few of these tools for manipulating and analyzing big data. I believe that these methods have a lot to offer and should be more widely known and used by economists.
We present the ‘NoSQL Injection Dataset for MongoDB, a comprehensive collection of data obtained from diverse projects focusing on NoSQL attacks on MongoDB databases.
In the present era, we can ...classify databases into three main types: structured, semi-structured, and unstructured. While structured databases have played a prominent role in the past, unstructured databases like MongoDB are currently experiencing remarkable growth. Consequently, the vulnerabilities associated with these databases are also increasing. Hence, we have gathered a comprehensive dataset comprising 400 NoSQL injection commands. These commands are segregated into two categories: 221 malicious commands and 179 benign commands. The dataset was meticulously curated by combining both manually authored commands and those acquired through web scraping from reputable sources. The collected dataset serves as a valuable resource for studying and analysing NoSQL injection vulnerabilities, offering insights into potential security threats and aiding in the development of robust protection mechanisms against such attacks. The dataset includes a blend of complex and simple commands that have been enhanced. The dataset is well-suited for machine learning and data analysis, especially for security enthusiasts. The security professionals can use this dataset to train or fine tune the AI-models or LLMs in order to achieve higher attack detection accuracy. The security enthusiasts can also augment this dataset to generate more NoSQL commands and create robust security tools.
Resumen: Desde hace varios años y de acuerdo con el Open Web Application Security Project Foundation (OWASP), el riesgo de inyección SQL ha estado liderando el listado de los 10 principales riesgos ...en aplicaciones web, para lo cual se requiere llevar a cabo proyectos que permitan analizar sus algoritmos de ataque como mecanismo de protección. Abstract: For several years and according to the Open Web Application Security Foundation (OWASP), the risk of SQL injection has been leading the list of the top 10 risks in web applications, for which it is required to carry out projects that allow to analyze its attack algorithms as a protection mechanism. De acuerdo con la Open Web Application Security Project Foundation (OWASP, 2013, 2017, 2020), el principal riesgo de las aplicaciones web son las inyecciones, las cuales ocurren cuando datos no confiables son enviados a un intérprete como parte de un comando o una consulta. Id ="1 and (select 9223372036854775807+1 from employee where emp_id=i UNICODE(SUBSTRING(emp_description,i,i)) =65)" Con esta inyección SQL, en una base de datos MYSQL, se generará un error si el primer carácter del campo emp_description del emp_id elegido es igual al carácter 'A' (en UNICODE es el número 65).
•Describes an instructional approach and exercises to introduce a data analytics tool into a course covering relational databases and structured query language (SQL).•We position SQL as the mental ...model for learning the data preparation and data blending features of a popular analytics tool, Alteryx.•We split the traditional SQL content from our course into four increments that increase in complexity.•For each increment, we use a multi-step approach to first develop students’ mental model of the SQL query code and then apply the mental model to the new environment of Alteryx.
This paper describes an instructional approach and exercises to introduce a data analytics tool into an existing course that covers relational databases and structured query language (SQL). SQL and relational databases are traditional topics in many AIS classes and are frequently taught with established technologies such as Microsoft Access. With the onset of newer data analytics tools, educators are faced with the challenge of incorporating emerging technologies while still covering basic foundational concepts. In this paper, we position SQL as the mental model for learning the data preparation and data blending features of a popular analytics tool, Alteryx. We split the traditional SQL content from our course into four increments that increase in complexity. For each increment, we use a multi-step approach to first develop students’ mental model of the SQL query code and then apply the mental model to the new environment of Alteryx. For each increment, students solve the same set of problems in SQL and Alteryx, so that the understanding of SQL eases the transition to Alteryx, and the practice in Alteryx reinforces the understanding of SQL.
Many intentionally vulnerable web applications are circulating on the Internet that serve as a legal test ground for practicing SQL injection attacks. For demonstration purposes the attacks will ...target an Acunetix test web application created using PHP programming language and MySQL relational database. In the practical part, the execution of the attack itself largely depends on the database management system, so the displayed syntax is intended only for the MySQL database management system. Example of an automated attack will be executed on SQLmap in a Linux Kali virtualized environment. Security guidelines with a purpose of protecting databases are also discussed.
Due to well-hidden and stage-triggered properties of second-order SQL injections in web applications, current approaches are ineffective in addressing them and still report high false negatives and ...false positives. To reduce false results, we propose a Proxy-based static analysis and dynamic execution mechanism towards detecting, locating and preventing second-order SQL injections (SQLPsdem). The static analysis first locates SQL statements in web applications and identifies all data sources and injection points (e.g., Post, Sessions, Database, File names) that injection attacks can exploit. After that, we reconstruct the SQL statements and use attack engines to jointly generate attacks to cover all the state-of-the-art attack patterns so as to exploit these applications. We then use proxy-based dynamic execution to capture the data transmitted between web applications and their databases. The data are the reconstructed SQL statements with variable values from the attack payloads. If a web application is vulnerable, the data will contain malicious attacks on the database. We match the data with rules formulated by attack patterns to detect first and second-order SQL injection vulnerabilities in web applications, particularly the second-order ones. We use a representative and complete coverage of attack patterns and precise matching rules to reduce false results. By escaping and truncating malicious payloads in the data transmitted from the web application to the database, we can eliminate the possible negative impact of the data on the database. In the evaluation, by generating 52,771 SQL injection attacks using four attack generators, SQLPsdem successfully detects 26 second-order (including 13 newly discovered ones) and 375 first-order SQL injection vulnerabilities in 12 open-source web applications. SQLPsdem can also 100% eliminate the malicious impact of the data with negligible overhead.
Intelligent transportation is an emerging technology that integrates advanced sensors, network communication, data processing, and automatic control technologies to provide great convenience for our ...daily lives. With the increasing popularity of intelligent transportation, its security issues have also attracted much attention. SQL injection attack is one of the most common attacks in the intelligent transportation system. It has characteristics of various types, fast mutations, hidden attacks, etc., and leads to great harm. Most of the current SQL detection methods are based on manually defined features. The detection results are heavily dependent on the accuracy of feature extraction, so it cannot cope with the increasingly complex SQL injection attacks in the intelligent transportation system. In order to solve this problem, this paper proposes a long short-term memory based SQL injection attack detection method, which can automatically learn the effective representation of data, and has a strong advantage to confront with complex high-dimensional massive data. In addition, this paper proposes an injection sample generation method based on data transmission channel from the perspective of penetration. This method can formally model SQL injection attack and generate valid positive samples. It can effectively solve the over-fitting problem caused by insufficient positive samples. The experimental results show that the proposed method improves the accuracy of the SQL injection attack detection and reduces the false positive rate, which is better than several related classical machine learning algorithms and commonly used deep learning algorithms.
Updated to include the new features introduced in PostgreSQL 13, this book shows you how to build better PostgreSQL applications and administer your PostgreSQL database efficiently. You'll master the ...advanced features of PostgreSQL and develop the skills you need to build secure and highly available database solutions.
SQL injection attack is the most serious security vulnerabilities on databases are connected with web or within an intranet, most of these vulnerabilities are affected by lack of input validation and ...SQL parameters are use. The attackers are trying to steal the data which was hidden and by attacking the database using the attacking technique that is called SQL injection attacks. The SQL injection attack detection and prevention technologies are experimented in this paper. There are different defence methods are used to prevent such as, parameterized statement, stored procedures and white list input validation. The comparative results of these methods are highlighted in the table with SQL injection query, prepared statement insertion and selection queries, stored procedures and modify queries. The comparison of these methods used for detection and prevention vulnerability in web server.
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