Semantic Machine Learning, Web Data Integration and Applications

According to the W3C, “The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries". It facilitates the integration of content and code among variety of protocols. This special issue will offer a platform to address all the related issues of Semantic Web along with the assisting advanced computing methods of machine learning and data integration in all major and potential areas. It will cover broad range of innovative research ideas and their implementations on various application domains. The scope of this issue will include the learning, analysis and synthesis of semantic web, respective programming, and applications with a particular focus on the principles, policies and practices. 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 Semantic Web Science and related technologies. It will aim to bring together leading researchers and practitioners in this field who are working on recent Semantic Web 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.

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

SCOPE:

Today’s 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: 

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.

Editor-in-Chief:

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

CONTACT:
Dr. Shishir Kumar Shandilya
Corresponding Guest Editor

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

shishir.sam@gmail.com