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Security on Web-Based Applications: Technologies, Methodologies, Analysis Methods and Recent Advances in Cybersecurity

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (30 April 2021) | Viewed by 13809

Special Issue Editors


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Guest Editor
Faculty of Engineering, Universidad Internacional de La Rioja, Av. de la Paz, 137, 26006 Logroño, La Rioja, Spain
Interests: optimization algorithms; computer security; software development methodologies, secure software development life cycle; malware analysis; mathematics; engineering problems; security on web-based applications

E-Mail Website
Guest Editor
Faculty of Engineering, Universidad Internacional de La Rioja, Av. de la Paz, 137, 26006 Logroño, La Rioja, Spain
Interests: computer security; secure software development life cycle; malware analysis; security on web-based applications; security on web services; machine learning for cybersecurity; attack pattern modeling; malware analysis, security analysis methods in web applications and web services; security analysis tools; benchmarking for web security

E-Mail Website
Guest Editor
Faculty of Engineering, Universidad Internacional de La Rioja, Av. de la Paz, 137, 26006 Logroño, La Rioja, Spain
Interests: computer security; secure software development life cycle; malware analysis; security on web-based applications; security on web services; machine learning for cybersecurity; attack patterns modeling; malware analysis, security analysis methods in web applications and web services; security analysis tools; benchmarking for web security

Special Issue Information

Dear Colleagues,

The continuous increase in the frequency and danger of attacks against the security of the information systems and the architectures that support them make it necessary to update and improve the methodologies related to the implementation and analysis of security and defense procedures, to provide greater security to online systems and applications of any type of organization.

To achieve this goal, it is necessary to start implementing security in web applications and web services from the beginning of its construction, using a “secure” software development life cycle (SSDLC). To adopt an SSDLC process, an improvement in security awareness is required at all departmental levels of any organization, whether public or private, and involves the carrying out of various security activities from the analysis and design phases, through implementation and testing to end the application deployed in the production phase. It is in the production phase that our Web applications architectures will be exposed to continuous attacks taking advantage of vulnerabilities not yet discovered. This Special Issue will provide a forum to present research papers showing advances in the defense techniques of web applications and web service architectures and technologies.

This Special Issue invites emerging topics related to the areas of implementation research and security test to fit in the scope of the journal and select high-quality research papers. The topics of interest include but are not limited to:

  • New implementations of “secure” SDLC processes for web applications and web services;
  • Threat modeling and derivation of security requirements tools and methods for web applications and web services;
  • Development of libraries for security validation of data in web application source codes;
  • Static analysis security tools (SAST) for web applications and web services;
  • Dynamic black box (DAST) and white box (IAST, RASP) security analysis tools;
  • Hybrid security analysis tools;
  • Security analysis methodologies for web applications and web services;
  • Forensic analysis in web applications;
  • Benchmarking to compare the effectiveness of static, dynamic or hybrid security analysis tools for web applications and web services;
  • Machine learning techniques for detecting anomalies in web applications and web services;
  • Development of new security requisites and specifications for emerging web applications and web services technologies and architectures;
  • Web applications attacks patterns modeling;
  • New security monitorization and visualization techniques, methods for web applications and web services;
  • Protection against malware on web resources;
  • Analysis and detection of web-based malware;
  • Malicious web content detection by machine learning

Prof. Dr. Juan Antonio Sicilia Montalvo
Prof. Dr. Juan Ramón Bermejo Higuera
Prof. Dr. Javier Bermejo Higuera
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • secure software development life cycle
  • security analysis
  • security validation
  • security on web-based applications
  • benchmarking
  • malware analysis
  • forensic analysis
  • anomalies detection
  • attacks patterns
  • security information visualization

Published Papers (2 papers)

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Research

45 pages, 764 KiB  
Article
Prevention and Fighting against Web Attacks through Anomaly Detection Technology. A Systematic Review
by Tomás Sureda Riera, Juan-Ramón Bermejo Higuera, Javier Bermejo Higuera, José-Javier Martínez Herraiz and Juan-Antonio Sicilia Montalvo
Sustainability 2020, 12(12), 4945; https://doi.org/10.3390/su12124945 - 17 Jun 2020
Cited by 17 | Viewed by 3910
Abstract
Numerous techniques have been developed in order to prevent attacks on web servers. Anomaly detection techniques are based on models of normal user and application behavior, interpreting deviations from the established pattern as indications of malicious activity. In this work, a systematic review [...] Read more.
Numerous techniques have been developed in order to prevent attacks on web servers. Anomaly detection techniques are based on models of normal user and application behavior, interpreting deviations from the established pattern as indications of malicious activity. In this work, a systematic review of the use of anomaly detection techniques in the prevention and detection of web attacks is undertaken; in particular, we used the standardized method of a systematic review of literature in the field of computer science, proposed by Kitchenham. This method is applied to a set of 88 papers extracted from a total of 8041 reviewed papers, which have been published in notable journals. This paper discusses the process carried out in this systematic review, as well as the results and findings obtained to identify the current state of the art of web anomaly detection. Full article
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16 pages, 3849 KiB  
Article
Computational System to Classify Cyber Crime Offenses using Machine Learning
by Rupa Ch, Thippa Reddy Gadekallu, Mustufa Haider Abidi and Abdulrahman Al-Ahmari
Sustainability 2020, 12(10), 4087; https://doi.org/10.3390/su12104087 - 16 May 2020
Cited by 69 | Viewed by 9117
Abstract
Particularly in the last decade, Internet usage has been growing rapidly. However, as the Internet becomes a part of the day to day activities, cybercrime is also on the rise. Cybercrime will cost nearly $6 trillion per annum by 2021 as per the [...] Read more.
Particularly in the last decade, Internet usage has been growing rapidly. However, as the Internet becomes a part of the day to day activities, cybercrime is also on the rise. Cybercrime will cost nearly $6 trillion per annum by 2021 as per the cybersecurity ventures report in 2020. For illegal activities, cybercriminals utilize any network computing devices as a primary means of communication with a victims’ devices, so attackers get profit in terms of finance, publicity and others by exploiting the vulnerabilities over the system. Cybercrimes are steadily increasing daily. Evaluating cybercrime attacks and providing protective measures by manual methods using existing technical approaches and also investigations has often failed to control cybercrime attacks. Existing literature in the area of cybercrime offenses suffers from a lack of a computation methods to predict cybercrime, especially on unstructured data. Therefore, this study proposes a flexible computational tool using machine learning techniques to analyze cybercrimes rate at a state wise in a country that helps to classify cybercrimes. Security analytics with the association of data analytic approaches help us for analyzing and classifying offenses from India-based integrated data that may be either structured or unstructured. The main strength of this work is testing analysis reports, which classify the offenses accurately with 99 percent accuracy. Full article
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