Search Results for author: A. Ercument Cicek

Found 3 papers, 3 papers with code

UnSplit: Data-Oblivious Model Inversion, Model Stealing, and Label Inference Attacks Against Split Learning

1 code implementation20 Aug 2021 Ege Erdogan, Alptekin Kupcu, A. Ercument Cicek

(1) We show that an honest-but-curious split learning server, equipped only with the knowledge of the client neural network architecture, can recover the input samples and obtain a functionally similar model to the client model, without being detected.

SplitGuard: Detecting and Mitigating Training-Hijacking Attacks in Split Learning

1 code implementation20 Aug 2021 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 utilization of the collective data of a group of data-holders.

Apollo: A Sequencing-Technology-Independent, Scalable, and Accurate Assembly Polishing Algorithm

1 code implementation12 Feb 2019 Can Firtina, Jeremie S. Kim, Mohammed Alser, Damla Senol Cali, A. Ercument Cicek, Can Alkan, Onur Mutlu

Our experiments with real read sets demonstrate that Apollo is the only algorithm that 1) uses reads from any sequencing technology within a single run and 2) scales well to polish large assemblies without splitting the assembly into multiple parts.

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