277 citations · 1.4k across the 59 of their papers we have counts for
13 papers · 1 filter
The Case for Retraining of ML Models for IoT Device Identification at the Edge
Roman Kolcun, Diana Andreea Popescu, Vadim Safronov +5
Internet-of-Things (IoT) devices are known to be the source of many security problems, and as such they would greatly benefit from automated management. This requires robustly iden…
Paralinguistic Privacy Protection at the Edge
Ranya Aloufi, Hamed Haddadi, David Boyle
Voice user interfaces and digital assistants are rapidly entering our lives and becoming singular touch points spanning our devices. These always-on services capture and transmit o…
Semi-supervised Federated Learning for Activity Recognition
Yuchen Zhao, Hanyang Liu, Honglin Li +2
Training deep learning models on in-home IoT sensory data is commonly used to recognise human activities. Recently, federated learning systems that use edge devices as clients to s…
Layer-wise Characterization of Latent Information Leakage in Federated Learning
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh +2
Training deep neural networks via federated learning allows clients to share, instead of the original data, only the model trained on their data. Prior work has demonstrated that i…
A Haystack Full of Needles: Scalable Detection of IoT Devices in the Wild
Said Jawad Saidi, Anna Maria Mandalari, Roman Kolcun +5
Consumer Internet of Things (IoT) devices are extremely popular, providing users with rich and diverse functionalities, from voice assistants to home appliances. These functionalit…
Running Neural Networks on the NIC
Giuseppe Siracusano, Salvator Galea, Davide Sanvito +4
In this paper we show that the data plane of commodity programmable (Network Interface Cards) NICs can run neural network inference tasks required by packet monitoring applications…