Abhinav Kumar 个人学术档案

202320247 11

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Reza TouraniAssistant Professor of Computer Science, Saint Louis University在 slu.edu 的电子邮件经过验证
Jie HouSaint Louis University在 slu.edu 的电子邮件经过验证
Srikathyayani SrikanteswaraIntel Corp.在 intel.com 的电子邮件经过验证
Mona VijIntel Labs在 intel.com 的电子邮件经过验证
Wei WangAssistant Professor, Saint Louis University在 slu.edu 的电子邮件经过验证
Dianshi YangUniversity of Delaware在 udel.edu 的电子邮件经过验证
Atena M.TabakhiWashington University in St. Louis在 wustl.edu 的电子邮件经过验证
Satyajayant "Jay" MisraProfessor of Computer Science and Electrical and Computer Engineering, New Mexico State University在 cs.nmsu.edu 的电子邮件经过验证
Miguel Antonio GuiraoNew Mexico State University在 nmsu.edu 的电子邮件经过验证

Abhinav Kumar

在 slu.edu 的电子邮件经过验证 - 首页


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
SCLERA: A Framework for Privacy-Preserving MLaaS at the Pervasive Edge A Kumar, R Tourani, M Vij, S Srikanteswara 2022 IEEE International Conference on Pervasive Computing and Communications …, 2022	9	2022
Iot sentinel: Correlation-based attack detection, localization, and authentication in iot networks D Yang, A Kumar, S Ray, W Wang, R Tourani 2023 32nd International Conference on Computer Communications and Networks …, 2023	7	2023
A Stealthy Inference Attack on Split Learning with a Split-Fuse Defensive Measure S Dougherty, A Kumar, J Hou, R Tourani, AM Tabakhi 2023 IEEE Conference on Communications and Network Security (CNS), 1-9, 2023	2	2023
Unveiling the Unseen: Exploring Whitebox Membership Inference through the Lens of Explainability C Li, A Kumar, Z Guo, J Hou, R Tourani arXiv preprint arXiv:2407.01306, 2024		2024
Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning N Sula, A Kumar, J Hou, H Wang, R Tourani arXiv preprint arXiv:2407.00866, 2024		2024
A Generative Framework for Low-Cost Result Validation of Machine Learning-as-a-Service Inference A Kumar, MAG Aguilera, R Tourani, S Misra Proceedings of the 19th ACM Asia Conference on Computer and Communications …, 2024		2024
Fides: A Generative Framework for Result Validation of Outsourced Machine Learning Workloads via TEE A Kumar, MAG Aguilera, R Tourani, S Misra arXiv preprint arXiv:2304.00083, 2023		2023

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