Search Results for author: Soteris Demetriou

Found 6 papers, 1 papers with code

Temporal Consistency Checks to Detect LiDAR Spoofing Attacks on Autonomous Vehicle Perception

no code implementations15 Jun 2021 Chengzeng You, Zhongyuan Hau, Soteris Demetriou

In particular, model-level LiDAR spoofing attacks aim to inject fake depth measurements to elicit ghost objects that are erroneously detected by 3D Object Detectors, resulting in hazardous driving decisions.

Autonomous Vehicles motion prediction

Quantifying and Localizing Private Information Leakage from Neural Network Gradients

no code implementations28 May 2021 Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou

In this paper, we introduce theoretically-motivated measures to quantify information leakages in both attack-dependent and attack-independent manners.

Layer-wise Characterization of Latent Information Leakage in Federated Learning

no code implementations17 Oct 2020 Fan Mo, Anastasia Borovykh, Mohammad Malekzadeh, Hamed Haddadi, Soteris Demetriou

Training deep neural networks via federated learning allows clients to share, instead of the original data, only the model trained on their data.

Federated Learning

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

2 code implementations12 Apr 2020 Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Soteris Demetriou, Ilias Leontiadis, Andrea Cavallaro, Hamed Haddadi

We present DarkneTZ, a framework that uses an edge device's Trusted Execution Environment (TEE) in conjunction with model partitioning to limit the attack surface against Deep Neural Networks (DNNs).

Image Classification

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