Introduction

With rapid development of big data storage and computing techniques, we have developed novel techniques beyond big data. Many aspects for both scientific research and people’s daily life have been influenced by big data based technology such as artificial intelligence, cloud computing, and Internet of Things. Providing security and privacy for big data storage, transmission, and processing have been attracting much attention in all big data related areas. IEEE Bigdatasecurity 2024 addresses this domain and aims to gather recent academic achievements in this field.

Security and robustness on Artificial Intelligence is the second concentration of IEEE Bigdatasecurity 2024. The emerging needs for building reliable and robust AI models in Big Data and Cloud environments with security and privacy guaranteed have attracted attention from a number of different perspectives. The new methods deployed in Big Data and Cloud environment have covered distinct dimensions, such as robust deep learning, secure deep learning/machine learning, multi-party computing, edge/fog computing, energy consumptions, high performance, and heterogeneous resources, cloud models, heterogeneous architecture, tele-health, resource allocation, load balance, multimedia, and QoS, etc.

Committee
General Chairs
Meikang Qiu, Augusta University, USA
Program Chairs
Yonghao Wang, Birmingham City University, UK
Xiaofu He, Columbia University, USA
Yongxin Zhu, Shanghai Advanced Research Institute, China
Industry Chair
Peng Zhang, SUNY Stony Brook, USA
Publicity Chairs
Bo Li, Beihang University, China
Keke Gai, Beijing Institute of Technology, China
Md Liakat Ali, Rider University, USA
Local Chairs
Gang Zeng, Nagoya University, Japan
Web Chair
Yunhe Feng, University of North Texas, USA
Financial Chair
Hui Zhao, Henan University, China
Award Chair
Sun-Yuan Kung, Princeton University, USA
Steering Committee
Meikang Qiu (Chair), Augusta University, USA
Sun-Yuan Kung, Princeton University, USA
Ruqian Lu, Chinese Academy of Sciences | CAS·Academy of Mathematics and Systems Science, China
Barbara Carminati, University of Insubria, Italy
Technical Program Committee
TBD

 

Call for paper

Important date

2024-02-01
Draft paper submission deadline

Many novel techniques and applications are invented based on the rapid development of big data. Today, some aspects for both scientific research and people’s daily life have been influenced by big data based technology such as artificial intelligence, cloud computing, and Internet of Things. Providing security and privacy for big data storage, transmission, and processing have been attracting much attention in all big data related areas. IEEE Bigdatasecurity 2024 addresses this domain and aims to gather recent academic achievements in this field.

Security and robustness on Artificial Intelligence is the second concentration of IEEE Bigdatasecurity 2024. The emerging needs for building reliable and robust AI models in Big Data and Cloud environments with security and privacy guaranteed have attracted attention from a number of different perspectives. The new methods deployed in Big Data and Cloud environment have covered distinct dimensions, such as robust deep learning, secure deep learning/machine learning, multi-party computing, edge/fog computing, energy consumptions, high performance, and heterogeneous resources, cloud models, heterogeneous architecture, tele-health, resource allocation, load balance, multimedia, and QoS, etc.

  • Artificial intelligence security
  • Novel big data security issues
  • Novel big data privacy issues
  • Blockchain-based security mechanism
  • Blockchain-based big data sharing
  • Security and privacy issues in blockchain
  • Big data security issues in IoT
  • Big data security issues in cloud computing
  • Big data privacy in cloud computing
  • Big data storage, integration, service, mining
  • Virtualization for big data on cloud
  • MapReduce with cloud for big data processing
  • Heterogeneous architecture for cloud computing
  • Dynamic resource sharing algorithm for cloud computing
  • Load balance for cloud computing
  • Mobile cloud computing
  • Mobile commerce security and privacy
  • Green cloud computing
  • Embedded system security
  • Cyber Security in emergent technologies
  • Cyber hacking, next generation fire wall
  • Cyber monitoring, incident response
  • Database security, data center security
  • Cyber threat intelligence
  • Sensor network security in cloud computing
  • Security policy and legal considerations
  • Cloud and networking security
  • Cloud computing and networking models
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Important Date
  • Conference Date

    May 10

    2024

    to

    May 12

    2024

  • Feb 01 2024

    Draft paper submission deadline

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