Special issue on Security, Privacy and Trust in network-based Big Data

The aim of the special issue is to present leading edge work concerning privacy protection issues and security challenges in the rapidly emerging field of network‐based Big Data. Research that addresses organisational and enterprise solutions for privacy protection and information security in Big Data environments will also be presented. Both papers dealing with fundamental theory, techniques, applications, and practical experiences concerning secure Big Data will be considered. The scope of the special issue includes (but is not limited to): − Security modelling and threat in Big Data − Auditing in network‐based Big Data − Access control mechanisms for Big Data systems − Secure Big Data resource virtualization mechanisms − Secure Big Data management outsourcing (e.g., database as a service) − Practical privacy and integrity mechanisms for outsourcing − Foundations of cloud‐centric threat models for Big Data − Trust and policy management − Secure identity management mechanisms − New Big Data web service security paradigms and mechanisms − Business and security risk models and clouds − Cost and usability models and their interaction with security in Big Data systems − Remote data integrity protection − Data‐centric security and data classification − Secure Big Data in wireless environment − Risk analysis and risk management **Instructions to authors** Only high quality original work that has not been published or is not currently under review elsewhere will be considered. The submitted papers should be formatted according to the journal style Each paper should include a cover letter with the title, abstract, author names and the corresponding author's name and affiliation, indicating that the submission is for "Security, Privacy and trust in network‐based Big Data". A PDF version of each submitted paper with its serial number should also be forwarded to [email protected]. All submitted papers will be refereed based on originality, scientific quality and relevance to this Special Issue and will be accepted or rejected in line with the usual standards of the Information Sciences journal.