b'Hamed Haddadi'

research

∙ 12/27/2022

PRISM: Privacy Preserving Internet of Things Security Management

Consumer healthcare applications are gaining increasing popularity in ou...

Savvas Hadjixenophontos, et al. ∙

research

∙ 10/10/2022

Tango or Square Dance? How Tightly Should we Integrate Network Functionality in Browsers?

The question at which layer network functionality is presented or abstra...

Alex Davidson, et al. ∙

research

∙ 10/04/2022

Using Entropy Measures for Monitoring the Evolution of Activity Patterns

In this work, we apply information theory inspired methods to quantify c...

Yushan Huang, et al. ∙

research

∙ 08/22/2022

SoK: Machine Learning with Confidential Computing

Privacy and security challenges in Machine Learning (ML) have become a c...

Fan Mo, et al. ∙

research

∙ 08/09/2022

Privacy-Aware Adversarial Network in Human Mobility Prediction

As mobile devices and location-based services are increasingly developed...

Yuting Zhan, et al. ∙

research

∙ 07/10/2022

FIB: A Method for Evaluation of Feature Impact Balance in Multi-Dimensional Data

Errors might not have the same consequences depending on the task at han...

Xavier F. Cadet, et al. ∙

research

∙ 05/27/2022

Locally Authenticated Privacy-preserving Voice Input

Increasing use of our biometrics (e.g., fingerprints, faces, or voices) ...

Ranya Aloufi, et al. ∙

research

∙ 03/07/2022

Blocked or Broken? Automatically Detecting When Privacy Interventions Break Websites

A core problem in the development and maintenance of crowd-sourced filte...

Michael Smith, et al. ∙

research

∙ 02/16/2022

Towards Battery-Free Machine Learning and Inference in Underwater Environments

This paper is motivated by a simple question: Can we design and build ba...

Yuchen Zhao, et al. ∙

research

∙ 01/29/2022

BatteryLab: A Collaborative Platform for Power Monitoring

Advances in cloud computing have simplified the way that both software d...

Matteo Varvello, et al. ∙

research

∙ 01/19/2022

Privacy-Aware Human Mobility Prediction via Adversarial Networks

As various mobile devices and location-based services are increasingly d...

Yuting Zhan, et al. ∙

research

∙ 12/13/2021

Proof of Steak

We introduce Proof-of-Steak (PoS) as a fundamental net-zero block genera...

Jon Crowcroft, et al. ∙

research

∙ 12/12/2021

Pool-Party: Exploiting Browser Resource Pools as Side-Channels for Web Tracking

We identify a new class of side-channels in browsers that are not mitiga...

Peter Snyder, et al. ∙

research

∙ 10/26/2021

Rapid IoT Device Identification at the Edge

Consumer Internet of Things (IoT) devices are increasingly common in eve...

Oliver Thompson, et al. ∙

research

∙ 09/10/2021

Multimodal Federated Learning

Federated learning is proposed as an alternative to centralized machine ...

Yuchen Zhao, et al. ∙

research

∙ 07/21/2021

A Tandem Framework Balancing Privacy and Security for Voice User Interfaces

Speech synthesis, voice cloning, and voice conversion techniques present...

Ranya Aloufi, et al. ∙

research

∙ 05/28/2021

Quantifying Information Leakage from Gradients

Sharing deep neural networks' gradients instead of training data could f...

Fan Mo, et al. ∙

research

∙ 05/11/2021

Blocking without Breaking: Identification and Mitigation of Non-Essential IoT Traffic

Despite the prevalence of Internet of Things (IoT) devices, there is lit...

Anna Maria Mandalari, et al. ∙

research

∙ 05/09/2021

Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback

Recommender systems are commonly trained on centrally collected user int...

Lorenzo Minto, et al. ∙

research

∙ 04/29/2021

PPFL: Privacy-preserving Federated Learning with Trusted Execution Environments

We propose and implement a Privacy-preserving Federated Learning (PPFL) ...

Fan Mo, et al. ∙

research

∙ 04/01/2021

Configurable Privacy-Preserving Automatic Speech Recognition

Voice assistive technologies have given rise to far-reaching privacy and...

Ranya Aloufi, et al. ∙

research

∙ 01/01/2021

MoSen: Activity Modelling in Multiple-Occupancy Smart Homes

Smart home solutions increasingly rely on a variety of sensors for behav...

Yuting Zhan, et al. ∙

research

∙ 11/17/2020

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...

Roman Kolcun, et al. ∙

research

∙ 11/04/2020

Paralinguistic Privacy Protection at the Edge

Voice user interfaces and digital assistants are rapidly entering our ho...

Ranya Aloufi, et al. ∙

research

∙ 11/02/2020

Semi-supervised Federated Learning for Activity Recognition

The proliferation of IoT sensors and edge devices makes it possible to u...

Yuchen Zhao, et al. ∙

research

∙ 10/17/2020

Layer-wise Characterization of Latent Information Leakage in Federated Learning

Training a deep neural network (DNN) via federated learning allows parti...

Fan Mo, et al. ∙

research

∙ 09/04/2020

Running Neural Networks on the NIC

In this paper we show that the data plane of commodity programmable (Net...

Giuseppe Siracusano, et al. ∙

research

∙ 09/03/2020

A Haystack Full of Needles: Scalable Detection of IoT Devices in the Wild

Consumer Internet of Things (IoT) devices are extremely popular, providi...

Said Jawad Saidi, et al. ∙

research

∙ 08/05/2020

DANA: Dimension-Adaptive Neural Architecture for Multivariate Sensor Data

Current deep neural architectures for processing sensor data are mainly ...

Mohammad Malekzadeh, et al. ∙

research

∙ 07/29/2020

Privacy-preserving Voice Analysis via Disentangled Representations

Voice User Interfaces (VUIs) are increasingly popular and built into sma...

Ranya Aloufi, et al. ∙

research

∙ 04/12/2020

DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments

We present DarkneTZ, a framework that uses an edge device's Trusted Exec...

Fan Mo, et al. ∙

research

∙ 04/12/2020

PrivEdge: From Local to Distributed Private Training and Prediction

Machine Learning as a Service (MLaaS) operators provide model training a...

Ali Shahin Shamsabadi, et al. ∙

research

∙ 03/16/2020

Towards Automatic Identification and Blocking of Non-Critical IoT Traffic Destinations

The consumer Internet of Things (IoT) space has experienced a significan...

Anna Maria Mandalari, et al. ∙

research

∙ 03/14/2020

Decentralized Policy-Based Private Analytics

We are increasingly surrounded by applications, connected devices, servi...

Kleomenis Katevas, et al. ∙

research

∙ 11/14/2019

Privacy and Utility Preserving Sensor-Data Transformations

Sensitive inferences and user re-identification are major threats to pri...

Mohammad Malekzadeh, et al. ∙

research

∙ 10/20/2019

BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices

Recent advances in cloud computing have simplified the way that both sof...

Matteo Varvello, et al. ∙

research

∙ 09/18/2019

Emotion Filtering at the Edge

Voice controlled devices and services have become very popular in the co...

Ranya Aloufi, et al. ∙

research

∙ 09/10/2019

Privacy-Preserving Bandits

Contextual bandit algorithms (CBAs) often rely on personal data to provi...

Mohammad Malekzadeh, et al. ∙

research

∙ 08/09/2019

Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants

Voice-enabled interactions provide more human-like experiences in many p...

Ranya Aloufi, et al. ∙

research

∙ 07/13/2019

Towards Characterizing and Limiting Information Exposure in DNN Layers

Pre-trained Deep Neural Network (DNN) models are increasingly used in sm...

Fan Mo, et al. ∙

research

∙ 06/21/2019

Modeling and Forecasting Art Movements with CGANs

Conditional Generative Adversarial Networks (CGANs) are a recent and pop...

Edoardo Lisi, et al. ∙

research

∙ 02/19/2019

Zest: REST over ZeroMQ

In this paper, we introduce Zest (REST over ZeroMQ), a middleware techno...

John Moore, et al. ∙

research

∙ 02/01/2019

Privacy Against Brute-Force Inference Attacks

Privacy-preserving data release is about disclosing information about us...

Seyed Ali Osia, et al. ∙

research

∙ 10/26/2018

Mobile Sensor Data Anonymization

Data from motion sensors such as accelerometers and gyroscopes embedded ...

Mohammad Malekzadeh, et al. ∙

research

∙ 08/30/2018

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...

Kleomenis Katevas, et al. ∙

research

∙ 03/14/2018

An Analysis of Home IoT Network Traffic and Behaviour

Internet-connected devices are increasingly present in our homes, and pr...

Yousef Amar, et al. ∙

research

∙ 03/12/2018

Deep Learning in Mobile and Wireless Networking: A Survey

The rapid uptake of mobile devices and the rising popularity of mobile a...

Chaoyun Zhang, et al. ∙

research

∙ 02/21/2018

Protecting Sensory Data against Sensitive Inferences

There is growing concern about how personal data are used when users gra...

Mohammad Malekzadeh, et al. ∙

research

∙ 02/10/2018

Distributed One-class Learning

We propose a cloud-based filter trained to block third parties from uplo...

Ali Shahin Shamsabadi, et al. ∙

research

∙ 02/09/2018

Deep Private-Feature Extraction

We present and evaluate Deep Private-Feature Extractor (DPFE), a deep mo...

Seyed Ali Osia, et al. ∙

Hamed Haddadi

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