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Found 6 papers, 2 papers with code
ScionFL: Efficient and Robust Secure Quantized Aggregation
In this paper, we unite both research directions by introducing ScionFL, the first secure aggregation framework for FL that operates efficiently on quantized inputs and simultaneously provides robustness against malicious clients.
Fairness in the Eyes of the Data: Certifying Machine-Learning Models
We present a framework that allows to certify the fairness degree of a model based on an interactive and privacy-preserving test.
From IP ID to Device ID and KASLR Bypass (Extended Version)
Our work examines the generation of this field in Windows (versions 8 and higher), Linux and Android, and shows that the IP ID field enables remote servers to assign a unique ID to each device and thus be able to identify subsequent transmissions sent from that device.
Cryptography and Security D.4.6; E.3
SBFT: a Scalable and Decentralized Trust Infrastructure
SBFT is a state of the art Byzantine fault tolerant permissioned blockchain system that addresses the challenges of scalability, decentralization and world-scale geo-replication.
Distributed, Parallel, and Cluster Computing
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Deep learning models have been successfully applied to malware detection.
Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring
Unfortunately, once the models are sold they can be easily copied and redistributed.
