In the SecureSense system, the authors propose a machine learning methodology for data
aggregation that prioritizes privacy preservation while maintaining data utility. This approach …

An important topic addressed by the wireless sensor networks community over the last
several years is the in-network data aggregation. It is significant as well as a challenging …

An important topic addressed by the wireless sensor networks community over the last
several years is the in-net work data aggregation. It is significant as well as a challenging …

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 …

In this paper, we present a multidimensional, highly effective method for aggregating data for
wireless sensor networks while maintaining privacy. The suggested system is resistant to …

In this study, the authors introduce “SecureNetGAN,” a novel system designed to protect
wireless sensor networks (WSNs) from cyber threats through the use of generative …

In‐network data aggregation in wireless sensor networks (WSNs) is a technique aimed at
reducing the communication overhead—sensed data are combined into partial results at …

Some credible third parties collect and share mobile sensor data with users to enhance
scientific innovation. However, since the sensor data contains sensitive attributes, it may …

Providing efficient data aggregation while preserving data privacy in wireless sensor
networks (WSNs) is a challenging problem. Existing security schemes either incur high …

Privacy-preservation in data aggregation in large scale Internet of Things applications is
challenging. Sensitive data from a result of collecting sensor data needs attentions to …