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Title:Simulation of a Fixed-Magnitude Data Poisoning Attack in a Federated Learning Distributed Model
Authors:Maciej Kuczynski
Conference:ISD2026
Tags:federated learning, machine learning, mobile devices, poisoning attack and proof of concept
Abstract:
The abstract summarizes a Proof of Concept (PoC) of measuring the impact of stealth data poisoning with a fixed magnitude on a federated machine learning model. The model is created in Tensorflow Lite and is used to predict the strength of the mobile network. It operates on four physical mobile devices running the Android operating system, each representing a different mobile network. The experiment demonstrates the hardware and software setup (including limitations applied), initial results of accuracy and loss measurements, and indicates potential improvements for the future.
Simulation of a Fixed-Magnitude Data Poisoning Attack in a Federated Learning Distributed Model
Simulation of a Fixed-Magnitude Data Poisoning Attack in a Federated Learning Distributed Model
