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Ömer Faruk Tuna
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2020 – today
- 2024
- [j4]Ömer Faruk Tuna
, Fehmi Emre Kadan:
Security of AI-Driven Beam Selection for Distributed MIMO in an Adversarial Setting. IEEE Access 12: 42028-42041 (2024) - [c7]Jordi Pérez-Romero, Oriol Sallent, Irene Vilà, Elli Kartsakli, Ömer Faruk Tuna, Swarup Kumar Mohalik, Xin Tao:
Towards Trustworthy Reinforcement Learning-based Resource Management in Beyond 5G. EuCNC/6G Summit 2024: 806-811 - [i5]Ferhat Karakoç, Betül Güvenç Paltun, Leyli Karaçay, Ömer Faruk Tuna, Ramin Fuladi, Utku Gülen:
FASIL: A challenge-based framework for secure and privacy-preserving federated learning. IACR Cryptol. ePrint Arch. 2024: 1028 (2024) - 2023
- [j3]Ömer Faruk Tuna
, Ferhat Özgür Çatak, Mustafa Taner Eskil:
TENET: a new hybrid network architecture for adversarial defense. Int. J. Inf. Sec. 22(4): 987-1004 (2023) - [c6]Ömer Faruk Tuna, Fehmi Emre Kadan:
A Novel Method to Mitigate Adversarial Attacks on AI-Driven Power Allocation in D-MIMO. BlackSeaCom 2023: 336-341 - [c5]Elli Kartsakli
, Jordi Pérez-Romero, Oriol Sallent, Nikolaos G. Bartzoudis
, Valerio Frascella, Swarup Kumar Mohalik, Thiis Metsch, Angelos Antonopoulos, Ömer Faruk Tuna, Yansha Deng
, Xin Tao, Maria A. Serrano, Eduardo Quiñones:
AI-Powered Edge Computing Evolution for Beyond 5G Communication Networks. EuCNC/6G Summit 2023: 478-483 - [c4]Ömer Faruk Tuna, Fehmi Emre Kadan, Leyli Karaçay:
Practical Adversarial Attacks Against AI-Driven Power Allocation in a Distributed MIMO Network. ICC 2023: 759-764 - [c3]Ömer Faruk Tuna, Fehmi Emre Kadan:
A Flexible, Efficient and Robust Method for AI-driven Power Control in D-MIMO. MeditCom 2023: 56-61 - [i4]Ömer Faruk Tuna, Fehmi Emre Kadan, Leyli Karaçay:
Practical Adversarial Attacks Against AI-Driven Power Allocation in a Distributed MIMO Network. CoRR abs/2301.09305 (2023) - 2022
- [j2]Ömer Faruk Tuna
, Ferhat Özgür Çatak
, Mustafa Taner Eskil
:
Closeness and uncertainty aware adversarial examples detection in adversarial machine learning. Comput. Electr. Eng. 101: 107986 (2022) - [j1]Ömer Faruk Tuna
, Ferhat Özgür Çatak, Mustafa Taner Eskil:
Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples. Multim. Tools Appl. 81(8): 11479-11500 (2022) - [c2]Ömer Faruk Tuna, Ferhat Özgür Çatak, Mustafa Taner Eskil:
Unreasonable Effectiveness of Last Hidden Layer Activations for Adversarial Robustness. COMPSAC 2022: 1098-1103 - [i3]Ömer Faruk Tuna, Ferhat Özgür Çatak, Mustafa Taner Eskil:
Unreasonable Effectiveness of Last Hidden Layer Activations. CoRR abs/2202.07342 (2022) - 2021
- [i2]Ömer Faruk Tuna, Ferhat Özgür Çatak, Mustafa Taner Eskil:
Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples. CoRR abs/2102.04150 (2021) - 2020
- [i1]Ömer Faruk Tuna, Ferhat Özgür Çatak, Mustafa Taner Eskil:
Closeness and Uncertainty Aware Adversarial Examples Detection in Adversarial Machine Learning. CoRR abs/2012.06390 (2020)
2010 – 2019
- 2019
- [c1]Ilknur Karadeniz, Ömer Faruk Tuna, Arzucan Özgür:
BOUN-ISIK Participation: An Unsupervised Approach for the Named Entity Normalization and Relation Extraction of Bacteria Biotopes. BioNLP-OST@EMNLP-IJNCLP 2019: 150-157
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last updated on 2024-08-03 21:14 CEST by the dblp team
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