Mete Akgün

Eberhard Karls Universität Tübingen

H-index: 14

Europe-Germany

About Mete Akgün

Mete Akgün, With an exceptional h-index of 14 and a recent h-index of 10 (since 2020), a distinguished researcher at Eberhard Karls Universität Tübingen, specializes in the field of Privacy, Data Security, Applied Cryptography, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach

ppAURORA: Privacy Preserving Area Under Receiver Operating Characteristic and Precision-Recall Curves

Scalable RFID authentication protocol based on physically unclonable functions

P/Key: PUF based second factor authentication

A Privacy-Preserving Framework for Collaborative Machine Learning with Kernel Methods

A privacy-preserving scheme for smart grid using trusted execution environment

Bringing the Algorithms to the Data--Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC)

Efficient privacy-preserving whole-genome variant queries

Mete Akgün Information

University	Eberhard Karls Universität Tübingen
Position	___
Citations(all)	809
Citations(since 2020)	514
Cited By	495
hIndex(all)	14
hIndex(since 2020)	10
i10Index(all)	17
i10Index(since 2020)	10
Email	Access Email
University Profile Page	Eberhard Karls Universität Tübingen
Google Scholar	View Google Scholar Profile

Mete Akgün Skills & Research Interests

Privacy

Data Security

Applied Cryptography

Machine Learning

Top articles of Mete Akgün

Title	Journal	Author(s)	Publication Date
Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach		Nico Pfeifer Mete Akgün Ali Burak Ünal Sofiane Ouaari	2023/9/8
ppAURORA: Privacy Preserving Area Under Receiver Operating Characteristic and Precision-Recall Curves	Network and System Security	Nico Pfeifer Mete Akgün Ali Burak Ünal	2023/8/7
Scalable RFID authentication protocol based on physically unclonable functions	Computer Networks	Işıl Kurt Fatih Alagöz Mete Akgün	2023/7/1
P/Key: PUF based second factor authentication	Plos one	Ertan Uysal Mete Akgün	2023/2/9
A Privacy-Preserving Framework for Collaborative Machine Learning with Kernel Methods		Anika Hannemann Ali Burak Ünal Arjhun Swaminathan Erik Buchmann Mete Akgün	2023/11/1
A privacy-preserving scheme for smart grid using trusted execution environment	IEEE Access	Mete Akgün Elif Ustundag Soykan Gurkan Soykan	2023/1/16
Bringing the Algorithms to the Data--Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC)	arXiv preprint arXiv:2212.03481	Marius de Arruda Botelho Herr Michael Graf Peter Placzek Florian König Felix Bötte ...	2022/12/7
Efficient privacy-preserving whole-genome variant queries	Bioinformatics	Mete Akgün Nico Pfeifer Oliver Kohlbacher	2022/4/15
CECILIA: Comprehensive Secure Machine Learning Framework	arXiv preprint arXiv:2202.03023	Ali Burak Ünal Nico Pfeifer Mete Akgün	2022/2/7
Escaped: Efficient secure and private dot product framework for kernel-based machine learning algorithms with applications in healthcare	Proceedings of the AAAI Conference on Artificial Intelligence	Ali Burak Ünal Mete Akgün Nico Pfeifer	2021/5/18
Privacy preserving gaze estimation using synthetic images via a randomized encoding based framework		Efe Bozkir Ali Burak Ünal Mete Akgün Enkelejda Kasneci Nico Pfeifer	2020/6/2
Privacy-preserving SVM on outsourced genomic data via secure multi-party computation		Huajie Chen Ali Burak Ünal Mete Akgün Nico Pfeifer	2020/3/16
Eye tracking data collection protocol for VR for remotely located subjects using blockchain and smart contracts		Efe Bozkir Shahram Eivazi Mete Akgün Enkelejda Kasneci	2020/12/14
Identifying disease-causing mutations with privacy protection	Bioinformatics	Mete Akgün Ali Burak Ünal Bekir Ergüner Nico Pfeifer Oliver Kohlbacher	2020/11/1