●会议名称(中文)： 第三届国际云计算和大数据隐私和安全研讨会
●会议名称(英文)： The 3rd International Symposium on Privacy and Security in Cloud and Big Data (PriSec 2014)
●所属学科： 计算机应用技术,计算机网络,信息安全
●开始日期： 2014-12-03
●结束日期： 2014-12-05
●所在国家： 澳大利亚
●所在城市： 澳大利亚
●具体地点： Sydney, Australia
●主办单位： IEEE Computer Society
●组织结构
会议主席： Chita R. Das, Pennsylvania State University, USA Vijay Varadharajan, Macquarie University, Australia
●全文截稿日期： 2014-09-05
●会议网站： http://www.swinflow.org/confs/prisec2014/
●会议背景介绍：
Cloud Computing and Big Data are two emerging paradigms in the recent developments of information technology. Cloud Computing enables computing resources to be provided as IT services in a pay-as-you-go fashion with high efficiency and effectiveness. Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. With Variety/Volume/Velocity/Value/Veracity/, Big Data such as medical records need to be protected in an scalable and efficient way.
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 an important challenge for Big Data as estimated by IDC. In addition, Cloud Computing and Big Data are coming together in practice. As estimated by IDC, by 2020, about 40% data globally would be touched with Cloud Computing. Cloud Computing provides strong storage, computation and distributed capability in support of Big Data processing. As such, there is a strong demand to investigate information privacy and security challenges in both Cloud Computing and Big Data. This symposium aims at providing such forum for researchers, practitioners and developers from different background areas such as distributed computing, cloud computing, big data, database, data mining, information security and privacy protection areas to exchange the latest experience, research ideas and synergic research and development on fundamental issues and applications about security and privacy issues in cloud and big data environments. The symposium solicits high quality research results in all related areas.
●征文范围及要求：
The objective of this symposium is to invite authors to submit original manuscripts that demonstrate and explore current advances in all aspects of security and privacy in cloud computing environments. The symposium solicits novel papers on a broad range of topics, including but not limited to:
Track 1: Privacy and Security in Cloud
· Privacy modelling in cloud computing
· Privacy correlation between multiple services in cloud computing
· Trust based privacy protection in cloud computing
· Privacy categorisation in cloud computing
· Privacy models for outsourcing
· Privacy preserving data publishing on cloud
· User privacy, service providers privacy and cloud platform privacy
· Privacy requirements engineering on cloud
· Private information retrieval on cloud
· Privacy and security in personal health records on cloud
· Privacy mechanisms in cloud services
· Privacy aware scheduling in cloud
· Security models, levels and scenarios in cloud computing
· Secure identity management in clouds
· Secure data management in cloud computing
· Secure access to clouds
· Remote data integrity protection
· Securing distributed data storage in the cloud
· Data-centric security and data classification
· Cost and usability models related security issues in clouds
· Interaction security between usability models in cloud computing
· Secure Job deployment and scheduling on cloud
· Secure resource allocation and indexing
· User authentication and authorisation in cloud services
· Auditing in cloud computing
· Cloud threat models
· Multi-tenancy related security/privacy issues
· Security/privacy/trust issues in SaaS/PaaS/IaaS
· Secure virtual machine mechanisms in cloud computing
· Vulnerabilities in cloud infrastructure
· Vulnerabilities in MapReduce
· Fault tolerance, exception handling and reliability issues in cloud
· Application programming environment
Track 2: Privacy and Security in Big Data
· Secure quantum communications
· Privacy in Big Data applications and services
· Privacy in Big Data end-point input validation and filtering
· Privacy in Big Data integration and transformation
· Privacy in parallel and distributed computation
· Privacy in Big Data storage management
· Privacy in Big Data access control mechanisms
· Privacy in Big Data mining and analytics
· Privacy in Big Data sharing and visualization
· Big Data privacy policies and standards
· Security model and architecture for Big Data
· Data mining security for Big Data
· Software and system security for Big Data
· Cryptography in Big Data
· Visualizing large scale security data
· Threat detection using Big Data analytics
· Human computer interaction challenges for Big Data security
· Data protection, integrity standards and policies
· Security and legislative impacts for Big Data
· Managing user access for Big Data
· Scalability and auditing for Big Data
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