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As part of the submission process, authors are required to check off their submission's compliance with all of the following items, and submissions may be returned to authors that do not adhere to these guidelines.
  • The submission has not been previously published, nor is it before another journal for consideration (or an explanation has been provided in Comments to the Editor).
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  • The text adheres to the stylistic and bibliographic requirements outlined in the Author Guidelines.
  • Please ensure that all co-authors listed on the title page are added as contributors (with their e-mail address) on Step 3 of the submission process.

Advancements in AI and Nature-inspired Approaches for Web Data Security


Today‚Äôs world is witnessing a constant barrage of cyber-attacks in the form of ransom ware, phishing, malware, botnets, insider threat, and many others. The situation is untenable and getting worse day-by-day. The amount of data at risk is enormous and rapidly growing over time. Cyber adversaries are becoming more advanced often utilizing intelligent algorithms/technologies for stealing personal data, disrupting critical networks, and corrupting communications. Therefore, the prevalent focus is now on web data security defensive measures and risk mitigations to counter these ever-growing attacks and to make the digital world safe.  However, still there is no self-sustainable security mechanism which can deal with sudden changes in network and deal it with adaptive methodology of diagnosing the misconfiguration. Conflict Management and Resolution are also required to be dealt properly in real-time. These severe and yet important problems are required to be resolved in a more intelligent way. AI & Nature-inspired Computing can potentially be a robust solution to build a strong, adaptive, self-aware web security mechanism. Interestingly, these approaches are fundamentally tolerant to incompleteness of information while maintaining the cohesiveness of the system.


This special issue will offer a platform to address all the related issues of Web Data Security along with the assisting advanced computing methods of AI and Nature-inspired Computing in all major and potential areas. It will cover broad range of innovative research ideas and their implementations on various application domains. This issue will publish the note-worthy and pioneer research contributions from leading scholars from all over the world with comprehensive coverage of each specific topic, highlighting recent and future trends and describing the latest advances in AI and Nature-inspired Computing for Web Data Security and related technologies. It will aim to bring together leading researchers and practitioners in this field who are working on these technologies. It will be a good reference for the practitioners and students in similar fields, with an aim to promote, present and discuss on-going research in this area.



This special issue will focus on latest research results and exchange views on the future research directions. It invites the original contributions, but not limited to, the themes and topics in following areas of research:


  • Network and critical infrastructure security
  • Cryptography and its applications
  • Hardware Security
  • Software and system security
  • Web data analytics
  • Data-driven security and measurement studies
  • Adversarial reasoning
  • Malware analysis
  • Privacy-enhancing technologies and anonymity
  • Nature-inspired Approaches for Web Data Security
  • AI Security
  • Performance modeling, monitoring and evaluation
  • Security of Federated and cross-organizational Web applications
  • Service-oriented Web application approaches
  • Security Implementation Architectures




More information can be found on the journal website: 



Important Dates:

Manuscript submission deadline:

March 31, 2020

Notification of Acceptance/Rejection/Revision:

May 15, 2020

Submission of revised papers:

June 15, 2020

Final decision:

July 31, 2020

Publication Date:

September 01, 2020


Submission Instructions for Perspective Authors: 

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere. These submissions will be peer reviewed and only high quality submissions will be selected for journal publication.

Before submission authors should carefully read over the journal's Author Guidelines, which is available at http://riverpublishers.com/authors.php 

Manuscripts must be submitted through the editorial manager system https://www.journals.riverpublishers.com/index.php/JWE/login.  For further query or inquiries, please contact the corresponding Guest Editor.


Martin Gaedke, Chemnitz University of Technology, Germany

Geert-Jan Houben, Delft University of Technology, The Netherlands

Bebo White, Stanford University, USA

Guest Editors:

Dr. Shishir Kumar Shandilya, VIT Bhopal University, INDIA

Dr. Neal Wagner, Massachusetts Institute of Technology, USA

Prof. Atulya K Nagar, Liverpool Hope University, UK


Dr. Shishir Kumar Shandilya
Corresponding Guest Editor

Division Head, Cyber Security & Digital Forensics
Vellore Institute of Technology, VIT Bhopal University, INDIA


Knowledge Discovery on the Web

Knowledge discovery is an interdisciplinary area focusing upon methodologies for identifying valid, novel, potentially useful, and meaningful patterns from data, and currently is widespread in numerous fields, including science, engineering, healthcare, business, and medicine. Recently, the rapid growth of social networks and online services has entailed that knowledge discovery approaches focus on the World Wide Web (WWW), whose popular use as a global information system has led to a huge amount of digital data.

This special issue focuses on the field of knowledge discovery from digital data, paying particular attention to data mining, machine learning, and information retrieval methods, systems, and applications. This special issue aims to provide a venue to researchers, scientists, students, and practitioners involved in the fields of knowledge discovery on data mining, information retrieval, and the semantic Web, for presenting and discussing novel and emerging ideas.

Topics of interest include (but are not limited to):

  • Big data on the Web;
  • Deep learning on the Web;
  • Feature selection and the extraction of Web data;
  • Hierarchical categorization of Web data;
  • Linked Web data;
  • Machine learning applications on the Web;
  • Open Web data;
  • Semantic Web;
  • Semantics and ontology engineering for Web applications;
  • Social media mining;
  • Social media measures and applications;
  • Text categorization on the Web;
  • Text mining for Web applications;
  • Web data mining;
  • Web information filtering and retrieval;
  • Web personalization and recommendation.

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