Issue In Web Applications Research Articles

Detecting SQL injection attacks by binary gray wolf optimizer and machine learning algorithms

SQL injection is one of the important security issues in web applications because it allows an attacker to interact with the application's database. SQL injection attacks can be detected using machine learning algorithms. The effective features should be employed in the training stage to develop an optimal classifier with optimal accuracy. Identifying the most effective features is an NP-complete combinatorial optimization problem. Feature selection is the process of selecting the training dataset's smallest and most effective features. The main objective of this study is to enhance the accuracy, precision, and sensitivity of the SQLi detection method. In this study, an effective method to detect SQL injection attacks has been proposed. In the first stage, a specific training dataset consisting of 13 features was prepared. In the second stage, two different binary versions of the Gray-Wolf algorithm were developed to select the most effective features of the dataset. The created optimal datasets were used by different machine learning algorithms. Creating a new SQLi training dataset with 13 numeric features, developing two different binary versions of the gray wolf optimizer to optimally select the features of the dataset, and creating an effective and efficient classifier to detect SQLi attacks are the main contributions of this study. The results of the conducted tests indicate that the proposed SQL injection detector obtain 99.68% accuracy, 99.40% precision, and 98.72% sensitivity. The proposed method increases the efficiency of attack detection methods by selecting 20% of the most effective features.

Poor Coding Leads to DoS Attack and Security Issues in Web Applications for Sensors

As the SQL injection attack is still at the top of the list at Open Web Application Security Project (OWASP) for more than one decade, this type of attack created too many types of issues for a web application, sensors, or any similar type of applications, such as leakage of user private data and organization intellectual property, or may cause Distributed Denial of Service (DDoS) attacks. This paper focused on the poor coding or invalidated input field which is a big cause of services unavailability for web applications. Secondly, it focused on the selection of program created issues for the WebSocket connections between sensors and the webserver. The number of users is growing to use web applications and mobile apps. These web applications or mobile apps are used for different purposes such as tracking vehicles, banking services, online stores for shopping, taxi booking, logistics, education, monitoring user activities, collecting data, or sending any instructions to sensors, and social websites. Web applications are easy to develop with less time and at a low cost. Due to that, business community or individual service provider’s first choice is to have a website and mobile app. So everyone is trying to provide 24/7 services to its users without any downtime. But there are some critical issues of web application design and development. These problems are leading to too many security loopholes for web servers, web applications, and its user’s privacy. Because of poor coding and validation of input fields, these web applications are vulnerable to SQL Injection and other security problems. Instead of using the latest third-party frameworks, language for website development, and version database server, another factor to disturb the services of a web server may be the socket programming for sensors at the production level. These sensors are installed in vehicles to track or use them for booking mobile apps.

Vulnerability Assessment in Heterogeneous Web Environment Using Probabilistic Arithmetic Automata

In the current scenario most of the business enterprises are running through web applications. But the major drawback is that they fail to provide a secure environment. To overcome this security issue in web applications, there are many vulnerability detection tools are available at present. But these tools are not proactive and consistent as it does not adapt to all kinds of recent updates and is unable to track new emerging vulnerabilities. For the long-term functioning of a business enterprise, statistical data with efficient analytics on vulnerabilities is required to enhance its security impacts. Predictive Analytics is a powerful solution to effectively arm the recent incident response to modern-day threats. Predictive Analytics provides a proactive and decision-making approach and insights into how well security programs are working. It can also help to identify problem areas and can warn about imminent or active attacks in heterogeneous web applications to enhance the former features and analyze the origin and pattern of the attack in a more effective manner. The pattern analyzed through research is given as an input to the Machine Learning techniques such as Deterministic Arithmetic Automata (DAA), Probabilistic Arithmetic Automata (PAA) to predict the probabilistic value as an output. From the obtained probabilistic values, we can detect the cause of an attack, prevent the heterogeneous web application of business enterprises from further impacts and find the penetration level of an attack from web application to web service.

Automation of application‐level caching in a seamless way

SummaryMeeting performance and scalability requirements while delivering services is a critical issue in web applications. Recently, latency and cost of Internet‐based services are encouraging the use of application‐level caching to continue satisfying users' demands and improve the scalability and availability of origin servers. Application‐level caching, in which developers manually control cached content, has been adopted when traditional forms of caching are insufficient to meet such requirements. Despite its popularity, this level of caching is typically addressed in an ad hoc way, given that it depends on specific details of the application. Furthermore, it forces application developers to reason about a crosscutting concern, which is unrelated to the application business logic. As a result, application‐level caching is a time‐consuming and error‐prone task, becoming a common source of bugs. Among all the issues involved with application‐level caching, the decision of what should be cached must frequently be adjusted to cope with the application evolution and usage, making it a challenging task. In this paper, we introduce an automated caching approach to automatically identify application‐level cache content at runtime by monitoring system execution and adaptively managing caching decisions. Our approach is implemented as a framework that can be seamlessly integrated into new and existing web applications. In addition to the reduction of the effort required from developers to develop a caching solution, an empirical evaluation showed that our approach significantly speeds up and improves hit ratios with improvements ranging from 2.78% to 17.18%.

A Web Page Recommendation system using GA based biclustering of web usage data

The World Wide Web store, share, and distribute information in the large scale. There is large number of internet users on the web. They are facing many problems like information overload due to the significant and rapid growth in the amount of information and the number of users. As a result, how to provide web users with more exactly needed information is becoming a critical issue in web applications. Web mining extracts interesting pattern or knowledge from web data. It is classified into three types as web content mining, web structure, and web usage mining. Web usage mining is the process of extracting useful knowledge from the server logs. This useful knowledge can be applied to target marketing and in the design of web portals. It may give information that is useful for improving the services offered by web portals and information access and retrieval tools. In this paper we are introducing a new approach for web page recommendation and user profile generation. This approach makes use of evolutionary biclustering technique for web page recommendation. We have applied it on two different datasets. One is clickstream data and other is web access log file of KSV University. The final results are generated from optimal biclusters obtained from evolutionary biclustering.

Students’ View on the ICT Courses Specially-Designed for the Deaf Learners

Internet and Computers have become requirements of life, mainly because they present a doorway into the World Wide Web. This World Wide Web that delivers an online learning platform is a very essential technology. Therefore, the accessibility issue in Web applications is very crucial, particularly for the Deaf Learners. The main objective of this research is to study the Deaf Learners’ satisfaction and interests in the developed e-learning platform named e-HearMe, which offers ICT courses that are specially designed for these learners. This research applied the quantitative method, whereby a questionnaire for the students’ that acts as the research instrument was distributed to 3 schools. These 3 schools were selected as research locations for their ICT Courses that are offered for the Deaf, for the whole of Malaysia. Thus, a total of 72 Deaf Learners from the Higher Secondary Level of Form 4 and Form 5 are chosen as the research sample. In evaluating the questionnaires’ results, the students were satisfied with the existence of this online e-learning medium e-HearMe, stating that they could share and exchange knowledge of information on the various ICT courses, with other teachers and other students from all over Malaysia, regardless of educational purposes or social purposes.

Ontology-based representation of reusable security requirements for developing secure web applications

Security is the major issue in web applications and it should be carefully considered in all the phases of the software development life cycle. The security requirements should be elicited and analysed in the early stages of requirements engineering. They are elicited from different sources by using security requirements engineering methods. Ontology can be used as one of the sources to specify security requirements knowledge effectively, since it is a 'formal, explicit specification of shared concepts' and is reusable. But there are no standard or only primitive security requirements ontology is available for requirements engineering phase. In this paper, we proposed and created security requirements ontology for web applications. Hence, we can reuse the security requirements knowledge and specify security requirements for developing different web applications. The reusability and effectiveness of security requirements ontology are validated using querying method.

Modular and flexible causality control on the Web

Ajax allows JavaScript programmers to create interactive, collaborative, and user-centered Web applications, known as Web 2.0 Applications. These Web applications behave as distributed systems because processors are user machines that are used to send and receive messages between one another. Unsurprisingly, these applications have to address the same causality issues present in distributed systems like the need (a) to control the causality between messages sent and responses received and (b) to react to distributed causal relations. JavaScript programmers overcome these issues using rudimentary and alternative techniques that largely ignore the distributed computing theory. In addition, these techniques are not very flexible and need to intrusively modify these Web applications. In this paper, we study how causality issues affect these applications and present WeCa, a practical library that allows for modular and flexible control over these causality issues in Web applications. In contrast to current proposals, WeCa is based on (stateful) aspects, message ordering strategies, and vector clocks. We illustrate WeCa in action with several practical examples from the realm of Web applications. In addition, we evaluate our proposal with a third-party application and its performance.

Performance, scalability and reliability issues in web applications

PurposeThe primary purpose of this paper is to present a comprehensive strategy for performance, reliability and scalability (PSR) testing of multi‐tier web applications.Design/methodology/approachThe strategy for PSR testing is presented primarily through examination of the intangible knowledge base in the PSR testing field. The paper also draws on relevant recent work conducted in the area of software performance evaluation.FindingsThe study revealed that appropriate testing procedures are critical for the success of web‐based multi‐tier applications. However, there was little academic work that collectively focused on PSR testing issues. This paper provides step‐by‐step testing procedures to ensure that web‐based applications are functioning well to meet user demands.Research limitations/implicationsGiven the rapid changes in technology and business environments, more applied research will be needed in the area of PSR testing to ensure the successful functioning of web‐based applications. For future studies, structured interviews or case‐study methods could be employed to present the views of online companies.Originality/valueThis paper provides a comprehensive strategy and the suggested steps for managers and technical personnel to ensure that the multi‐tier, web‐based applications are effective, scalable and reliable.