Data Security and Management in Clouds
Deadline for submissions: 8 Jan 2021
Notification of First Round: 8 Mar 2021 or before
Final Decision: 30 Jun 2021
About the issue
Cloud computing is one of the fastest growing technologies, and many enterprises, especially small and medium sized enterprises, have considered deploying their IT resource on the cloud due to its scalability, elasticity and low cost. However, while enterprises migrate their IT resource into cloud, privacy and security issues are raised. Firstly, the cloud users will loss control on their data when they migrate to cloud, they neither do have control over the cloud infrastructure, nor can monitor configuration and policy controls of cloud. So, it is essential that cloud providers ensure, and cloud users do believe, that security and privacy safeguards are in place. Secondly, the cloud, aggregating massive amount of confidential data of numerous organizations, become a very attractive target for hackers. security situational awareness will detect and warn for vulnerabilities for cloud, and help benefit the cloud providers as well as enterprise users.
This special issue is dedicated to the identification of techniques that make the cloud more secure and trusted. We also solicit techniques that enable cloud security situation aware both based on insider forensics and perimeter traffic. A key focus will be on the integration of theoretical foundations with the practical real-life applications that make cloud provide greater guarantees to end users about the security of their services and data.
Topics including (but not limited to) the following:
Security modelling and threat analysis in the Cloud for Enterprises
Authentication and authorization in the Cloud for Enterprises
Security Situational Awareness based on Big Data and management (e.g. Cloud traffic, or security (log) data in the Cloud) for Enterprises
Security-focused Service Level Agreements
Data privacy and management in the Cloud for Enterprises
Recovery and fault tolerance for Enterprises
Security and Privacy solutions for migrating Cloud solutions to Blockchain platforms for Enterprises
Cyber security attacks using machine learning (ML) methods against real-world Cloud-based AI solutions for Enterprises
Original papers describing completed and unpublished work not currently under review by any other journal/magazine/conference/workshop are solicited. Previously published conference/symposia/workshop papers or technical reports MUST be clearly clarified by the authors (at the submission stage) and an explanation should be provided how such papers have been extended to be considered for this special issue.
Prospective authors should submit via the submission site of Enterprise Information Systems. Submitting authors must answer ‘Yes’ to a question of “Is this submission for a special issue?” and then select “Cloud Security and Big Data” from the drop-down menu.
Yong Zhang, College of Electronic and Information Engineering, Shenzhen University, China (firstname.lastname@example.org)
Lei Pan, School of Information Technology, Deakin University, Australia (email@example.com)