This is the repository for Project of COMP 530 Data Privacy and Security course given by Emre Gursoy at Koc University. Code is written by Esad Simitcioglu, Arman Torikoglu, and Alireza Khodaie
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Updated
Jan 26, 2023 - Jupyter Notebook
This is the repository for Project of COMP 530 Data Privacy and Security course given by Emre Gursoy at Koc University. Code is written by Esad Simitcioglu, Arman Torikoglu, and Alireza Khodaie
DSPLab@UMich-Dearborn Website
Distributed DP-Helmet: Scalable Differentially Private Non-interactive Averaging of Single Layers
Trustworthy AI/ML course by Professor Birhanu Eshete, University of Michigan, Dearborn.
O objetivo deste projeto de iniciação científica é estudar a área de Privacy Preserving Machine Learning (PPML), que se dedica a encontrar soluções para realizar aprendizado de máquina de forma segura e preservando a privacidade dos dados.
Birhanu Eshete is an Associate Professor of Computer Science at the University of Michigan, Dearborn. His main research focus is in trustworthy machine learning with emphasis on security, safety, privacy, interpretability, fairness, and the dynamics thereof. He also studies online cybercrime and advanced and persistent threats (APTs).
Implementation of privacy-preserving SVM assuming public model private data scenario
Extremely Randomized Trees with Privacy Preservation for Distributed Data (k-PPD-ERT)
Similarity Guided Model Aggregation for Federated Learning
Source Code for the Paper "Does CLIP Know my Face?" (Demo: https://huggingface.co/spaces/AIML-TUDA/does-clip-know-my-face)
This repository contains personal notes and summaries on Secure and Private AI
FedAnil+ is a novel lightweight, and secure Federated Deep Learning Model to address non-IID data, privacy concerns, and communication overhead. This repo hosts a simulation for FedAnil+ written in Python.
Python Privacy framework
Stash of some of the most potent research papers, blogs and videos on AI which I liked.
Crypto-Convolutional Neural Network library written on top of SEAL 2.3.1
Git-Repository for Research Project Re-Identification Attacks on Smartwatch Health Data
FedAnil is a secure blockchain-enabled Federated Deep Learning Model to address non-IID data and privacy concerns. This repo hosts a simulation for FedAnil written in Python.
Privacy Preserving Neural Networks (PPNN): Repo for Capstone Project at Ashoka
A more detailed description on the HPE Swarm Learning Installation guide. Official repo can be viewed on the url below:
A Learning Journal on (Privacy-Preserving) AI for Medicine and Healthcare
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