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 2026 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 2026. 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.
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