IMPACTS OF ADVERSARIAL MACHINE LEARNING METHODS IN DEEP LEARNING MODELS USED IN IOT ENVIRONMENTS
Ph.D
Saved in:
Main Author: | ABHIJIT SINGH |
---|---|
Other Authors: | ELECTRICAL & COMPUTER ENGINEERING |
Format: | Theses and Dissertations |
Language: | English |
Published: |
2023
|
Subjects: | |
Online Access: | https://scholarbank.nus.edu.sg/handle/10635/246241 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | National University of Singapore |
Language: | English |
Similar Items
-
Using machine learning to detect vulnerabilities in Internet of Things (IoT) devices
by: Yong, Li Yao
Published: (2024) -
Challenges and countermeasures for adversarial attacks on deep reinforcement learning
by: Ilahi, Inaam, et al.
Published: (2022) -
Privacy Risks of Securing Machine Learning Models against Adversarial Examples
by: Liwei Song, et al.
Published: (2020) -
TOWARDS ADVERSARIAL ROBUSTNESS OF DEEP VISION ALGORITHMS
by: YAN HANSHU
Published: (2022) -
A Survey on IoT Security: Application Areas, Security Threats, and Solution Architectures
by: Hassija, V., et al.
Published: (2021)