In recent years, security and privacy concerns with online social networks (OSN) have becoming a key research area. Since the popularity of OSN Websites such as Facebook, Twitter, Linkedin, etc has grown enormously and playing a significant role among the Internet community. The concept of applying a computational intelligence (CI) approaches in social network analysis is feasible and sound. Moreover, CI and its associated learning paradigms are playing vital characteristics in large number of application areas related to security and privacy in information systems. CI paradigm consists of various branches that are not limited to expert systems, artificial immune system, swarm intelligence, fuzzy system, neural network, evolutionary computing and various hybrid systems, which are combinations of two or more branches. We expect this special issue intends to bring together the state-of-art practices on security and privacy aspects has been addressed from CI perspective, with a focus on simulations of social networks, representation, applications/tools and analysis of social networks which will be the open avenues of future research.

We invite researchers to contribute original research articles as well as review articles that will seek the continuing efforts to understand the CI techniques that lead to future improvements for social networks security and privacy.

Topics of Interest

The topics relevant to this special issue include but are not limited to:

Social networking security and privacy concepts and applications
Social network modelling and security issues
Information revelation and privacy in online social networks
Social networking data analysis tools and services
Machine learning to gain novel insights on social network security analysis
Evolutionary algorithms for learning the behaviour and privacy analysis in social networks
Evolutionary algorithms for mining social networks for decision support
Mining and analyzing social data for decision support & optimization
Optimization of dynamic processes in social networks
Computational Intelligence Solutions to security and privacy issues in mobile social networking
Large-scale graph algorithms for social network analysis
Chaos theory and chaotic systems for social media content security
Soft computing technologies for both quantitative and qualitative security assessment and privacy management in online social networks
Artificial neural network and neural system applied to social media and mitigating the privacy risks of social networking

Paper Selection:

Papers must be tailored to the emerging fields of Computational Intelligence paradigms into Security and Privacy for Online Social Networks (OSNs) and explicitly consider recent deployments models, challenges and novel solutions. The editors maintain the right to reject papers they deem to be out of scope of this special issue. Only originally unpublished contributions and invited articles will be considered for the issue. Each paper will go through a rigorous peer-review process by at least three international reviewers. Submissions must be made through http://ees.elsevier.com/fgcs

Please choose "SI: Security&Privacy in OSNs" when reaching the step of selecting article type name in submission process.

Lead Editor:

Dr. B.B. Gupta, National Institute of Technology, Kurukshetra, India
Email: bbgupta.nitkkr@gmail.com

Guest Editors:

Dr. Arun Kumar Sangaiah, VIT University, Vellore, India
Email: arunkumarsangaiah@gmail.com

Dr. Nadia Nedjah, State University of Rio de Janeiro, Brazil
Email: nadia@eng.uerj.br

Dr. Shingo Yamaguchi, Yamaguchi University, Japan
Email: shingo@yamaguchi-u.ac.jp

Dr. Zhiyong Zhang, Henan University of Science & Technology, China
Email: xidianzzy@126.com

Dr. Michael Sheng, University of Adelaide, Adelaide, Australia
Email: michael.sheng@adelaide.edu.au

Important Dates

Manuscripts Due: October 01, 2016

First Decision Date: December 31, 2016

Revision Due: February 15, 2017

Final Decision Date: April 30, 2017

Final Paper Due: May 30, 2017