Recent developments in machine learning (ML) allow for efficient data stream processing
and also help in meeting various privacy requirements. Traditionally, predefined privacy …

Data sensing and gathering is an essential task for various information-driven services in
smart cities. On the one hand, Internet of Things (IoT) sensors can be deployed at certain …

This article proposes a sensor data anonymization model that is trained on decentralized
data and strikes a desirable trade-off between data utility and privacy, even in …

The growing number of Internet of Things (IoT) devices generates massive amounts of
diverse data, including personal or confidential information (ie, sensory, images, etc.) that is …

Generative models have shown great promise in synthesizing high-quality time-series data
that resemble the sensor data generated by mobile and IoT devices, but do not reveal the …

Data privacy and protection through anonymization is a critical issue for network operators
or data owners before it is forwarded for other possible use of data. With the adoption of …

Customized healthcare should organize an environment for the manipulation of reliable and
secure private data. Using Generative Adversarial Networks (GANs), this paper proposes a …

A Complete Bibliography of ACM Transactions on Internet of Things (TIOT) Page 1 A
Complete Bibliography of ACM Transactions on Internet of Things (TIOT) Nelson HF Beebe …