Essays about: "Adversarial attacks"
Showing result 1 - 5 of 33 essays containing the words Adversarial attacks.
-
1. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. READ MORE
-
2. Attack Strategies in Federated Learning for Regression Models : A Comparative Analysis with Classification Models
University essay from Umeå universitet/Institutionen för tillämpad fysik och elektronikAbstract : Federated Learning (FL) has emerged as a promising approach for decentralized model training across multiple devices, while still preserving data privacy. Previous research has predominantly concentrated on classification tasks in FL settings, leaving a noticeable gap in FL research specifically for regression models. READ MORE
-
3. Adversarial robustness of STDP-trained spiking neural networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Adversarial attacks on machine learning models are designed to elicit the wrong behavior from the model. One such attack on image classifiers are maliciously crafted inputs that, to the human eye, look untampered with but have been carefully altered to cause misclassification. READ MORE
-
4. Exploring GANs to generate attack-variations in IoT networks
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Data driven IDS development requires a vast amount of data to be effective against future attacks and a big problem is the lack of available data. This thesis explores the use of GANs (Generative adversarial networks) in generating attack data that can be used as apart of a training set for an IDS to improve the robustness against adversarial attacks. READ MORE
-
5. Adversarial Machine (Deep) Learning-basedRobustification in 5G Networks
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : A significant development in wireless communication and artificial intelligence has been made possible by the combination of 5G networks with deep learning methods. This paper explores the complex interactions between these areas, concentrating on the dangers that adversarial attacks represent in the context of 5G network slicing. READ MORE
