Bigdata 2015 - Special Issue on Security and Privacy in Big Data Clouds

The rapid development of digital sensors, networks, and smart devices long with their extensive use is leading to the creation of huge collections of data, and coins the term Big Data. Big Data is characterized by the integration of a significant amount of data, of varying modalities or types, at a pace that cannot be handled by traditional data management systems. Since huge amounts of data in unstructured and semi-structured forms are being generated from various sources, new platforms, frameworks and methodologies are required for to data management, data safety and data analytics.
Cloud Computing enables computing resources to be provided as IT services in a pay-as-you-go fashion with high efficiency and effectiveness. Cloud-based platforms with overwhelming advantages over traditional platforms are increasingly utilized as potential hosts for Big Data. However, information privacy and security is one of most concerned issues for Cloud Computing due to its open environment with very limited user-side control. It is also a great challenge for Big Data. Especially on cloud-based platforms, there are two important aspects of Big Data Security. One is how to protect Big Data, the other is how to using Big Data analytic technique to enhance security of the whole system. Current work on Big Data focuses on information processing such as data mining and analysis. However, security and privacy of Big Data are vital concerns that have received less research focus. The aim of this special issue is to solicit both original research and tutorial articles that discuss the security and privacy of Big Data within the cloud.
Topics of Interest
Any topic related to security and privacy aspects, e.g., access control, authorization, authorization, risk analysis, and anonymization, for Big Data and cloud computing, will be considered. All aspects of design, theory and realization are of interest. The scope and interests for the special issue include but are not limited to the following list:
(i) Fundamentals and Technologies for Data Forensics in Big Data Environment
Architectures for Big Data
Big Data Analytics
Federal Big Data
Big Data & Bioinformatics
Big Data Search & Sharing;
Data Management Applications and Services
Cloud Federation and Hybrid Cloud Infrastructure
Cloud Architecture, Configuration, Performance, and Capacity Management
Cloud Resource Virtualization and Composition
Green Cloud Computing
Storage, Data, and Analytics Clouds
Cloud Application Benchmarks, Programming Models and Tools
(ii) Security and Privacy in Cloud Computing
Accountability and Audit in clouds
Authentication and Authorization in Cloud Services
Secure Access to Clouds
Cryptography for/in the Cloud
Secure Identity Management in Clouds
Secure Data Management in Cloud Computing
Secure Virtual Machine Mechanisms in Cloud Computing
Fault-Tolerance and Reliability for Cloud Services and Applications
Privacy Modeling and Engineering in Cloud Computing
Private Information Retrieval on Cloud
Multi-Tenancy Related Security/Privacy Issues
Security/Privacy/Trust Issues in SaaS/PaaS/IaaS
(iii) Security and Privacy in Big Data
Security Model and Architecture for Big Data
Software and System Security for Big Data
Cryptography in Big Data
Scalability and Auditing for Big Data
Security and Privacy in Big Data Sharing and Visualization
Security and Privacy in Big Data Access Control
Security and Privacy in Big Data Mining and Analytics
Data-Centric Security and Data Classification
Privacy in Big Data Applications and Services
Privacy in Big Data Integration and Transformation
Privacy in Big Data Storage Management
Big Data Privacy Policies and Standards
(iv) System, Information and Network Security
High Performance Security Systems
Secure System Implementation
Database and System Security
Cryptographic Primitives and Security Protocols
Disaster Recovery
Provable Security
Intrusion Detection and Prevention
Privacy, Anonymity and Traceability
Identity Management
Access Controls and Security Mechanisms
Web & Applications Security
Secure Routing and Network Management
Network Security Policies
Submission Format and Guideline
All submitted papers must be clearly written in excellent English and contain only original work, which has not been published by or is currently under review for any other journal or conference. Papers must not exceed 25 pages (one-column, at least 11pt fonts) including figures, tables, and references. A detailed submission guideline is available as “Guide to Authors” at: http://www.elsevier.com/journals/future-generation...
All manuscripts and any supplementary material should be submitted through Elsevier Editorial System (EES). The authors must select “SI: S&P in Big Data Clouds” when they reach the “Article Type” step in the submission process. The EES website is located at: ees.elsevier.com/fgcs
All papers will be peer-reviewed by at least three independent reviewers. Requests for additional information should be addressed to the guest editors.
Guest Editors
Qin Liu (corresponding guest editor)
gracelq628-AT-126.com
Avinash Srinivasan
avinash-AT-temple.edu
Jiankun Hu
J.Hu-AT-adfa.edu.au
Guojun Wang
csgjwang-AT-gmail.com
Important dates
Submission deadline: November 15, 2015
First-roundpass notification: November 30, 2015
Review result notification: April 1, 2016
Acceptance/rejection notification: July 1, 2016
Publication: December, 2016