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 2020 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 2020. 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.
- Novel big data model
- Big data security issues in IoT
- Big data privacy issues in IoT
- Big data security issues in cloud computing
- Big data privacy in cloud computing
- Big data storage, integration, service, mining
- Blockchain-based security mechanism
- Blockchain-based big data sharing
- Security and privacy issues in blockchain
- Cyber hacking, next generation fire wall
- Cyber monitoring, incident response
- Database security, data center security
- Social engineering, insider threats, advance spear phishing
- Cyber threat intelligence
- Security and fault tolerance for embedded or ubiquitous systems
- Tele-health security in cloud computing
- Sensor network security in cloud computing
- Security policy and legal considerations
- Cloud and networking security
- Cloud computing and networking models
- 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 networks and sensor network optimizations
- Cyber Security in emergent technologies
