Traffic analysis is the process of monitoring network activities, discovering specific patterns,
and gleaning valuable information from network traffic. It can be applied in various fields …

Federated learning (FL) has nourished a promising method for data silos, which enables
multiple participants to construct a joint model collaboratively without centralizing data. The …

Removing information from a machine learning model is a non-trivial task that requires to
partially revert the training process. This task is unavoidable when sensitive data, such as …

Learning to reject is a special kind of self-awareness (the ability to know what you do not
know), which is an essential factor for humans to become smarter. Although machine …

Data is the foundation of most science. Unfortunately, sharing data can be obstructed by the
risk of violating data privacy, impeding research in fields like healthcare. Synthetic data is a …

Deploying machine learning models in production may allow adversaries to infer sensitive
information about training data. There is a vast literature analyzing different types of …

The right to be forgotten requires the removal or" unlearning" of a user's data from machine
learning models. However, in the context of Machine Learning as a Service (MLaaS) …

While the 5G is being rolled out in different industrial sectors, the 6G is expected to
implement data-driven ubiquitous machine learning for industrial information integration …

Owning to the massive growth in internet connectivity, smartphone technology, and digital
tools, the use of various online social networks (OSNs) has significantly increased. On the …

Recent years have seen the emergence of practical advanced cryptographic tools that not
only protect data privacy and authenticity, but also allow for jointly processing data from …