Exploiting epistemic uncertainty of the deep learning models to generate
adversarial samples

Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples

8 February 2021

Ömer Faruk Tuna

Ferhat Ozgur Catak

Papers citing "Exploiting epistemic uncertainty of the deep learning models to generate adversarial samples"

11 / 11 papers shown

Title
Relationship between Uncertainty in DNNs and Adversarial Attacks Abigail Adeniran Adewale Adeyemo Adewale Adeyemo AAML 20 0 0 20 Sep 2024
Practical Adversarial Attacks Against AI-Driven Power Allocation in a Distributed MIMO Network Ömer Faruk Tuna Fehmí Emre Kadan Leyli Karaçay AAML 14 6 0 23 Jan 2023
Defensive Distillation based Adversarial Attacks Mitigation Method for Channel Estimation using Deep Learning Models in Next-Generation Wireless Networks Ferhat Ozgur Catak Murat Kuzlu Evren Çatak Umit Cali Ozgur Guler AAML 17 26 0 12 Aug 2022
MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for multiple uncertainty types and tasks Gianni Franchi Xuanlong Yu Andrei Bursuc Ángel Tena Rémi Kazmierczak Séverine Dubuisson Emanuel Aldea David Filliat UQCV 23 28 0 02 Mar 2022
The Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retraining Murat Kuzlu Ferhat Ozgur Catak Umit Cali Evren Çatak Ozgur Guler AAML 24 9 0 16 Feb 2022
Security Concerns on Machine Learning Solutions for 6G Networks in mmWave Beam Prediction Ferhat Ozgur Catak Evren Çatak Murat Kuzlu Umit Cali Devrim Unal AAML 35 44 0 09 May 2021
Adversarial Machine Learning Security Problems for 6G: mmWave Beam Prediction Use-Case Evren Çatak Ferhat Ozgur Catak A. Moldsvor AAML 19 22 0 12 Mar 2021
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 276 5,661 0 05 Dec 2016
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 264 3,110 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 285 9,138 0 06 Jun 2015