82 citations · 117 across the 4 of their papers we have counts for
4 papers
SplitOut: Out-of-the-Box Training-Hijacking Detection in Split Learning via Outlier Detection
Ege Erdogan, Unat Teksen, Mehmet Salih Celiktenyildiz +2
Split learning enables efficient and privacy-aware training of a deep neural network by splitting a neural network so that the clients (data holders) compute the first layers and o…
SplitGuard: Detecting and Mitigating Training-Hijacking Attacks in Split Learning
Ege Erdogan, Alptekin Kupcu, A. Ercument Cicek
Distributed deep learning frameworks such as split learning provide great benefits with regards to the computational cost of training deep neural networks and the privacy-aware uti…
UnSplit: Data-Oblivious Model Inversion, Model Stealing, and Label Inference Attacks Against Split Learning
Ege Erdogan, Alptekin Kupcu, A. Ercument Cicek
Training deep neural networks often forces users to work in a distributed or outsourced setting, accompanied with privacy concerns. Split learning aims to address this concern by d…
Demo -- Zelig: Customizable Blockchain Simulator
Ege Erdogan, Can Arda Aydin, Oznur Ozkasap +1
As blockchain-based systems see wider adoption, it becomes increasingly critical to ensure their reliability, security, and efficiency. Running simulations is an effective method o…