A unified framework for privacy-preserving data analysis and machine learning

SRDS 2020: End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things

C3-SL: Circular Convolution-Based Batch-Wise Compression for Communication-Efficient Split Learning (IEEE MLSP 2022)

reveal the vulnerabilities of SplitNN

Comparison b/w Federated Learning & Split Learning for credit card fraud detection dataset using Pytorch

Source codes of paper "Can We Use Split Learning on 1D CNN for Privacy Preserving Training?"

Official Repository for ResSFL (accepted by CVPR '22)

Enhancing Efficiency in Multidevice Federated Learning through Data Selection

Framework that supports pipeline federated split learning with multiple hops.

Split Learning Simulation Framework for LLMs

Supplementary code for the paper "SplitGuard: Detecting and MitigatingTraining-Hijacking Attacks in Split Learning"

Official code of the paper "A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning".

testing adhocSL

Simple Split Learning setup. Proof of Concept & testbed

Official code for "EC-SNN: Splitting Deep Spiking Neural Networks on Edge Devices" (IJCAI2024)

Split learning for privacy-preserving healthcare, and threats and defensive techniques for decentralized learning. (with Prof. Vinay Chamola)

Framework of Distributed Learning in Vehicular Networks

CycleSL: Server-Client Cyclical Update Driven Scalable Split Learning