Call for Papers

As the advances of Internet technology, the cyberspace generates a staggering volume of data, and the capacity to electronically store, transfer and process those data continues to grow exponentially. Recently, Big data has emerged as a new technology in response to this situation. However, Big data is a double-edged sword: leveraging it will drive competitive advantage; ignoring it will risk enterprise of lagging behind the competition. For enterprises, two potential threats from big data in cyberspace are identified: the .first one is from the enterprise data released to public, which are subjected to legal requirements for privacy before they can be made available to other parties; the second one is from the data about the enterprise on social networks, which have a strong influence on a brand reputation that most enterprises should not ignore.

For the first threat from the collected data, as most collected information contains private or sensitive information, how to release them while preserving privacy is an important issue that need to be addressed.

For the second threat from cyberspace, it has been reported that online astroturfers have been hired to post product comments on different social networks. They can also act maliciously by spreading negative or false information about competitors. For an enterprise, a serious and important research issue is to identify the abnormal contents on social networks and collect the evidence of astroturfers behaviors. If enterprises do not manage their online reputation properly, they risk damaging their brand and sales assets. Hence the battlefield to do so is clearly played out in the cyberspace.

Recent years have witnessed increasing research attention on Curbing Cyber Crimes including the detection of online astroturfers. This trend raises the need for launching the special issue on Curbing Cyber Crimes in Cyberspace. This issue will be the premier forum in which privacy preservation and online astroturfers detection are promoted as serious and important research fields with relevant challenging problems and emerging issues to be formally addressed. We aim to increase potential collaborations and partnerships by bringing together academic researchers and industry practitioners from data mining, network security, digital forensics, behavioral and psychology sciences with the objectives to present updated research efforts and progresses on foundational and emerging topics, exchange new ideas and identify future research directions.

In addition to selected top quality papers accepted and presented in the ATIS-2015 (http://www.atis2015.conferences.academy/) and 2015 International Workshop on Curbing Cyber Crimes (C3-2015), we welcome any original high-quality research papers in methods, theories, techniques and tools for advancing the Securing Cyberspace

All submissions will be rigidly peer reviewed to guarantee the quality. This special issue will focus on but not limited to the following topics: 

(1) Data Privacy
  • Differential Privacy
  • Graph Differential Privacy
  • Privacy Preserving Data Release
  • Privacy Preserving Web Services
(2) Content Based Methods: Information / Opinion / Knowledge Modeling 
     and Spread Analysis
  • Agent-based data retrieval
  • Complex sequence analysis
  • Content and Opinion analysis
  • Temporal-sequential pattern mining
  • Impact-oriented pattern mining
  • Event/activity/action filtering
  • Multi-granularity data visualization

(3) Behavior Based Methods: Behavior Modeling and Mining
  • Behavior structure extraction
  • Behavior life cycles
  • Sequential/Parallel/Distributed behavior modeling
  • Behavior dynamics
  • Cyber Criminal behavior analysis
  • Social networking behavior analysis
(4) Social Relation Based Methods: Cyber Analysis
  • Group and group behavior detection, tracking and recognition
  • Collusive crime/piracy detection
  • Graph-based behavior/social modeling
  • Dynamic/hidden group presentation
  • Collaborative social recommendation
  • Group interaction, collaboration, representation and pro.ling
  • Cyber-Gossip Spread Models

(5) Applications and Open Case Study
  • Poster spam detection
  • Blog spam detection
  • Click spam detection
  • Identity authentication
  • Botnets prevention
  • Datasets for cyber-gossips detection

(6) Curbing Collusive Cyber Crimes
  • Cyber-Gossip Spread Models
  • Identity authentication
  • Datasets for cyber-gossips detection
  • Collusive crime/piracy detection