
-
MoSen: Activity Modelling in Multiple-Occupancy Smart Homes
Smart home solutions increasingly rely on a variety of sensors for behav...
read it
-
The Case for Retraining of ML Models for IoT Device Identification at the Edge
Internet-of-Things (IoT) devices are known to be the source of many secu...
read it
-
Paralinguistic Privacy Protection at the Edge
Voice user interfaces and digital assistants are rapidly entering our ho...
read it
-
Semi-supervised Federated Learning for Activity Recognition
The proliferation of IoT sensors and edge devices makes it possible to u...
read it
-
Layer-wise Characterization of Latent Information Leakage in Federated Learning
Training a deep neural network (DNN) via federated learning allows parti...
read it
-
Running Neural Networks on the NIC
In this paper we show that the data plane of commodity programmable (Net...
read it
-
A Haystack Full of Needles: Scalable Detection of IoT Devices in the Wild
Consumer Internet of Things (IoT) devices are extremely popular, providi...
read it
-
DANA: Dimension-Adaptive Neural Architecture for Multivariate Sensor Data
Current deep neural architectures for processing sensor data are mainly ...
read it
-
Privacy-preserving Voice Analysis via Disentangled Representations
Voice User Interfaces (VUIs) are increasingly popular and built into sma...
read it
-
DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments
We present DarkneTZ, a framework that uses an edge device's Trusted Exec...
read it
-
PrivEdge: From Local to Distributed Private Training and Prediction
Machine Learning as a Service (MLaaS) operators provide model training a...
read it
-
Towards Automatic Identification and Blocking of Non-Critical IoT Traffic Destinations
The consumer Internet of Things (IoT) space has experienced a significan...
read it
-
Decentralized Policy-Based Private Analytics
We are increasingly surrounded by applications, connected devices, servi...
read it
-
Privacy and Utility Preserving Sensor-Data Transformations
Sensitive inferences and user re-identification are major threats to pri...
read it
-
BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices
Recent advances in cloud computing have simplified the way that both sof...
read it
-
Emotion Filtering at the Edge
Voice controlled devices and services have become very popular in the co...
read it
-
Privacy-Preserving Bandits
Contextual bandit algorithms (CBAs) often rely on personal data to provi...
read it
-
Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants
Voice-enabled interactions provide more human-like experiences in many p...
read it
-
Towards Characterizing and Limiting Information Exposure in DNN Layers
Pre-trained Deep Neural Network (DNN) models are increasingly used in sm...
read it
-
Modeling and Forecasting Art Movements with CGANs
Conditional Generative Adversarial Networks (CGANs) are a recent and pop...
read it
-
Zest: REST over ZeroMQ
In this paper, we introduce Zest (REST over ZeroMQ), a middleware techno...
read it
-
Privacy Against Brute-Force Inference Attacks
Privacy-preserving data release is about disclosing information about us...
read it
-
Mobile Sensor Data Anonymization
Data from motion sensors such as accelerometers and gyroscopes embedded ...
read it
-
Finding Dory in the Crowd: Detecting Social Interactions using Multi-Modal Mobile Sensing
Remembering our day-to-day social interactions is challenging even if yo...
read it
-
An Analysis of Home IoT Network Traffic and Behaviour
Internet-connected devices are increasingly present in our homes, and pr...
read it
-
Deep Learning in Mobile and Wireless Networking: A Survey
The rapid uptake of mobile devices and the rising popularity of mobile a...
read it
-
Protecting Sensory Data against Sensitive Inferences
There is growing concern about how personal data are used when users gra...
read it
-
Distributed One-class Learning
We propose a cloud-based filter trained to block third parties from uplo...
read it
-
Deep Private-Feature Extraction
We present and evaluate Deep Private-Feature Extractor (DPFE), a deep mo...
read it
-
Replacement AutoEncoder: A Privacy-Preserving Algorithm for Sensory Data Analysis
An increasing number of sensors on mobile, Internet of things (IoT), and...
read it
-
Privacy-Preserving Deep Inference for Rich User Data on The Cloud
Deep neural networks are increasingly being used in a variety of machine...
read it
-
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics
The increasing quality of smartphone cameras and variety of photo editin...
read it
-
Kissing Cuisines: Exploring Worldwide Culinary Habits on the Web
Food and nutrition occupy an increasingly prevalent space on the web, an...
read it
-
Valorising the IoT Databox: Creating Value for Everyone
The Internet of Things (IoT) is expected to generate large amounts of he...
read it