41 citations · 102 across the 17 of their papers we have counts for
17 papers
Understanding the Privacy Risks of Popular Search Engine Advertising Systems
Salim Chouaki, Oana Goga, Hamed Haddadi +1
We present the first extensive measurement of the privacy properties of the advertising systems used by privacy-focused search engines. We propose an automated methodology to study…
GT-TSCH: Game-Theoretic Distributed TSCH Scheduler for Low-Power IoT Networks
Omid Tavallaie, Seid Miad Zandavi, Hamed Haddadi +1
Time-Slotted Channel Hopping (TSCH) is a synchronous medium access mode of the IEEE 802.15.4e standard designed for providing low-latency and highly-reliable end-to-end communicati…
Towards Machine Learning and Inference for Resource-constrained MCUs
Yushan Huang, Hamed Haddadi
Machine learning (ML) is moving towards edge devices. However, ML models with high computational demands and energy consumption pose challenges for ML inference in resource-constra…
Survey of Federated Learning Models for Spatial-Temporal Mobility Applications
Yacine Belal, Sonia Ben Mokhtar, Hamed Haddadi +2
Federated learning involves training statistical models over edge devices such as mobile phones such that the training data is kept local. Federated Learning (FL) can serve as an i…
Federated and distributed learning applications for electronic health records and structured medical data: A scoping review
Siqi Li, Pinyan Liu, Gustavo G. Nascimento +12
Federated learning (FL) has gained popularity in clinical research in recent years to facilitate privacy-preserving collaboration. Structured data, one of the most prevalent forms…
Analysing Fairness of Privacy-Utility Mobility Models
Yuting Zhan, Hamed Haddadi, Afra Mashhadi
Preserving the individuals' privacy in sharing spatial-temporal datasets is critical to prevent re-identification attacks based on unique trajectories. Existing privacy techniques…
Protected or Porous: A Comparative Analysis of Threat Detection Capability of IoT Safeguards
Anna Maria Mandalari, Hamed Haddadi, Daniel J. Dubois +1
Consumer Internet of Things (IoT) devices are increasingly common, from smart speakers to security cameras, in homes. Along with their benefits come potential privacy and security…
Information Theory Inspired Pattern Analysis for Time-series Data
Yushan Huang, Yuchen Zhao, Alexander Capstick +3
Current methods for pattern analysis in time series mainly rely on statistical features or probabilistic learning and inference methods to identify patterns and trends in the data.…
PRISM: Privacy Preserving Healthcare Internet of Things Security Management
Savvas Hadjixenophontos, Anna Maria Mandalari, Yuchen Zhao +1
Consumer healthcare Internet of Things (IoT) devices are gaining popularity in our homes and hospitals. These devices provide continuous monitoring at a low cost and can be used to…
Tango or Square Dance? How Tightly Should we Integrate Network Functionality in Browsers?
Alex Davidson, Matthias Frei, Marten Gartner +5
The question at which layer network functionality is presented or abstracted remains a research challenge. Traditionally, network functionality was either placed into the core netw…
Privacy-Aware Adversarial Network in Human Mobility Prediction
Yuting Zhan, Hamed Haddadi, Afra Mashhadi
As mobile devices and location-based services are increasingly developed in different smart city scenarios and applications, many unexpected privacy leakages have arisen due to geo…
Machine Learning with Confidential Computing: A Systematization of Knowledge
Fan Mo, Zahra Tarkhani, Hamed Haddadi
Privacy and security challenges in Machine Learning (ML) have become increasingly severe, along with ML's pervasive development and the recent demonstration of large attack surface…
Nitriding: A tool kit for building scalable, networked, secure enclaves
Philipp Winter, Ralph Giles, Moritz Schafhuber +1
Enclave deployments often fail to simultaneously be secure (e.g., resistant to side channel attacks), powerful (i.e., as fast as an off-the-shelf server), and flexible (i.e., uncon…
On-Device Voice Authentication with Paralinguistic Privacy
Ranya Aloufi, Hamed Haddadi, David Boyle
Using our voices to access, and interact with, online services raises concerns about the trade-offs between convenience, privacy, and security. The conflict between maintaining pri…
Towards Battery-Free Machine Learning and Inference in Underwater Environments
Yuchen Zhao, Sayed Saad Afzal, Waleed Akbar +5
This paper is motivated by a simple question: Can we design and build battery-free devices capable of machine learning and inference in underwater environments? An affirmative answ…
Quantifying and Localizing Usable Information Leakage from Neural Network Gradients
Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh +3
In collaborative learning, clients keep their data private and communicate only the computed gradients of the deep neural network being trained on their local data. Several recent…
Stronger Privacy for Federated Collaborative Filtering with Implicit Feedback
Lorenzo Minto, Moritz Haller, Hamed Haddadi +1
Recommender systems are commonly trained on centrally collected user interaction data like views or clicks. This practice however raises serious privacy concerns regarding the reco…