Enhancing the Security of Collaborative Deep Neural Networks: An Examination of the Effect of Low Pass Filters

Author:

Adeyemo Adewale A.1ORCID,Hasan Syed Rafay1ORCID

Affiliation:

1. Tennessee Technological University, Cookeville, TN, USA

Funder

Tennessee Tech University's Center for Manufacturing Research

National Science Foundation

Publisher

ACM

Reference35 articles.

1. A. Adeyemo , F. Khalid , T. Odetola , and S. R. Hasan , " Security analysis of capsule network inference using horizontal collaboration," in 2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS) , pp. 1074 -- 1077 , IEEE , 2021 . A. Adeyemo, F. Khalid, T. Odetola, and S. R. Hasan, "Security analysis of capsule network inference using horizontal collaboration," in 2021 IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 1074--1077, IEEE, 2021.

2. A. Olatunji I. Bhattacharya W.Adepoju E. N. Esfahani and T. Banik "Application of artificial intelligence in optimization of solid state transformer core for modern electric vehicles using multi-objective genetic algorithm " in 2022 IEEE Vehicle Power and Propulsion Conference (VPPC) pp. 1--7 IEEE 2022. A. Olatunji I. Bhattacharya W.Adepoju E. N. Esfahani and T. Banik "Application of artificial intelligence in optimization of solid state transformer core for modern electric vehicles using multi-objective genetic algorithm " in 2022 IEEE Vehicle Power and Propulsion Conference (VPPC) pp. 1--7 IEEE 2022.

3. H. Gao , Y. Tian , R. Yao , F. Xu , X. Fu , and S. Zhong , " Exploiting adversarial examples to drain computational resources on mobile deep learning systems," in 2020 IEEE/ACM Symposium on Edge Computing (SEC) , pp. 334 -- 339 , IEEE , 2020 . H. Gao, Y. Tian, R. Yao, F. Xu, X. Fu, and S. Zhong, "Exploiting adversarial examples to drain computational resources on mobile deep learning systems," in 2020 IEEE/ACM Symposium on Edge Computing (SEC), pp. 334--339, IEEE, 2020.

4. CoEdge: Cooperative DNN Inference With Adaptive Workload Partitioning Over Heterogeneous Edge Devices

5. MoDNN: Local distributed mobile computing system for Deep Neural Network

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