8 research outputs found
BAGEL: Backdoor Attacks against Federated Contrastive Learning
Federated Contrastive Learning (FCL) is an emerging privacy-preserving
paradigm in distributed learning for unlabeled data. In FCL, distributed
parties collaboratively learn a global encoder with unlabeled data, and the
global encoder could be widely used as a feature extractor to build models for
many downstream tasks. However, FCL is also vulnerable to many security threats
(e.g., backdoor attacks) due to its distributed nature, which are seldom
investigated in existing solutions. In this paper, we study the backdoor attack
against FCL as a pioneer research, to illustrate how backdoor attacks on
distributed local clients act on downstream tasks. Specifically, in our system,
malicious clients can successfully inject a backdoor into the global encoder by
uploading poisoned local updates, thus downstream models built with this global
encoder will also inherit the backdoor. We also investigate how to inject
backdoors into multiple downstream models, in terms of two different backdoor
attacks, namely the \textit{centralized attack} and the \textit{decentralized
attack}. Experiment results show that both the centralized and the
decentralized attacks can inject backdoors into downstream models effectively
with high attack success rates. Finally, we evaluate two defense methods
against our proposed backdoor attacks in FCL, which indicates that the
decentralized backdoor attack is more stealthy and harder to defend
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Single-pixel reconstructive mid-infrared micro-spectrometer.
Miniaturized spectrometers in the mid-infrared (MIR) are critical in developing next-generation portable electronics for advanced sensing and analysis. The bulky gratings or detector/filter arrays in conventional micro-spectrometers set a physical limitation to their miniaturization. In this work, we demonstrate a single-pixel MIR micro-spectrometer that reconstructs the sample transmission spectrum by a spectrally dispersed light source instead of spatially grated light beams. The spectrally tunable MIR light source is realized based on the thermal emissivity engineered via the metal-insulator phase transition of vanadium dioxide (VO2). We validate the performance by showing that the transmission spectrum of a magnesium fluoride (MgF2) sample can be computationally reconstructed from sensor responses at varied light source temperatures. With potentially minimum footprint due to the array-free design, our work opens the possibility where compact MIR spectrometers are integrated into portable electronic systems for versatile applications
Supplementary document for Single-Pixel Reconstructive Mid-Infrared Micro-Spectrometer - 6326855.pdf
Supplementary Material