A Review of Confidentiality Threats Against Embedded Neural Network Models
Authors: Raphaël Joud, Pierre-Alain Moellic, Rémi Bernhard, Jean-Baptiste Rigaud | Published: 2021-05-04
Fast, Reliable, and Secure Drone Communication: A Comprehensive Survey
Authors: Vikas Hassija, Vinay Chamola, Adhar Agrawal, Adit Goyal, Nguyen Cong Luong, Dusit Niyato, F. Richard Yu, Mohsen Guizani | Published: 2021-05-04
Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX
Authors: Chengliang Zhang, Junzhe Xia, Baichen Yang, Huancheng Puyang, Wei Wang, Ruichuan Chen, Istemi Ekin Akkus, Paarijaat Aditya, Feng Yan | Published: 2021-05-04 | Updated: 2021-11-08
Quantifying the Tradeoff Between Cybersecurity and Location Privacy
Authors: Dajiang Suo, M. Elena Renda, Jinhua Zhao | Published: 2021-05-04 | Updated: 2021-12-10
GRNN: Generative Regression Neural Network — A Data Leakage Attack for Federated Learning
Authors: Hanchi Ren, Jingjing Deng, Xianghua Xie | Published: 2021-05-02 | Updated: 2022-09-12
Analysis of Machine Learning Approaches to Packing Detection
Authors: Charles-Henry Bertrand Van Ouytsel, Thomas Given-Wilson, Jeremy Minet, Julian Roussieau, Axel Legay | Published: 2021-05-02
Who’s Afraid of Adversarial Transferability?
Authors: Ziv Katzir, Yuval Elovici | Published: 2021-05-02 | Updated: 2022-10-06
AirMixML: Over-the-Air Data Mixup for Inherently Privacy-Preserving Edge Machine Learning
Authors: Yusuke Koda, Jihong Park, Mehdi Bennis, Praneeth Vepakomma, Ramesh Raskar | Published: 2021-05-02
Privacy and Integrity Preserving Training Using Trusted Hardware
Authors: Hanieh Hashemi, Yongqin Wang, Murali Annavaram | Published: 2021-05-01
Adversarial Example Detection for DNN Models: A Review and Experimental Comparison
Authors: Ahmed Aldahdooh, Wassim Hamidouche, Sid Ahmed Fezza, Olivier Deforges | Published: 2021-05-01 | Updated: 2022-01-07