活动简介

Recent rapid development of the intelligent data has enabled a dramatic influence of using big data in various domains, such as smart city and smart cloud. The concept of the intelligent data has been remarkably paid attentions by both academia and industries. The approach of gaining intelligent meta data processing is still at the exploring stage and the research concentrations are varied, such as intelligent data modeling, energy-aware meta data processing, and intelligent data mining. Moreover, the security issue is a critical concern of applying intelligent data from both data protection and data correction perspectives. Gathering contemporary research achievements in the field is greatly significant for the research. We aim to collect the latest achievements and exchange research ideas in the domains of intelligent data and security at this academic event. Joining IDS 2016 will be a great opportunity for your to reach academics, professionals, and vendors who have the same research interests as yours. IEEE IDS 2016 will be held at Columbia University’s Schapiro Center.

征稿信息

征稿范围

The objective of IEEE IDS 2016 is to provide a forum for scientists, engineers, and researchers to discuss and exchange their new ideas, novel results, work in progress and experience on all aspects of smart computing and cloud computing. Topics of particular interest include, but are not limited to:

  • Security in new paradigms of intelligent data
  • Cyber hacking, next generation fire wall of intelligent data
  • Cyber monitoring and incident response in intelligent data
  • Digital forensics in intelligent data
  • Big data security, Database security
  • Intelligent database
  • Intelligent data mining
  • Social engineering, insider threats, advance spear phishing
  • Cyber threat intelligence
  • Security and fault tolerance for embedded or ubiquitous systems
  • Cloud-based intelligent data and security issues
  • Tele-health security in intelligent data
  • Sensor network security
  • Embedded networks and sensor network optimizations
  • Cloud computing and networking models
  • Heterogeneous architecture for cloud-based intelligent data
  • Dynamic resource sharing algorithm for cloud-based intelligent data
  • Load balance for cloud-based intelligent data
  • Cloud-based audio/video streaming techniques
  • MapReduce in intelligent data
  • Visualization in intelligent data
  • Cloud-based real-time multimedia techniques in intelligent data
  • Mobile cloud computing
  • Green cloud computing
  • Quality of Service (QoS) improvements techniques
  • Case studies for various applications
  • Cyber Security in emergent technologies, infrastructures and applications
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重要日期
  • 会议日期

    04月09日

    2016

    04月10日

    2016

  • 04月10日 2016

    注册截止日期

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