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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.
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.
application that uses homomorphic encryption and Luhn's algorithm to validate credit card numbers without exposing actual card details. This provides a privacy-preserving method to verify sensitive information without compromising security.
Intel Paillier Cryptosystem Library is an open-source library which provides accelerated performance of a partial homomorphic encryption (HE), named Paillier cryptosystem, by utilizing Intel® IPP-Crypto technologies on Intel CPUs supporting the AVX512IFMA instructions. The library is written in modern standard C++ and provides the essential API …
This project explores and implements various techniques and protocols using SageMath. It covers topics such as Elliptic Curve Diffie-Hellman (ECDH) key exchange, homomorphic encryption, secure multi-party computation (MPC), queueing theory analysis, and RSA cryptanalysis.
Implementation of a client reputation, gradient checking and homomorphic encryption mechanism to defend a federated learning system from data/model poisoning and reverse engineering attacks.