I know what you trained last summer: A survey on stealing machine learning models and defences
Machine-Learning-as-a-Service (MLaaS) has become a widespread paradigm, making
even the most complex Machine Learning models available for clients via, eg, a pay-per …
even the most complex Machine Learning models available for clients via, eg, a pay-per …
Adversarial machine learning in wireless communications using RF data: A review
D Adesina, CC Hsieh, YE Sagduyu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Machine learning (ML) provides effective means to learn from spectrum data and solve
complex tasks involved in wireless communications. Supported by recent advances in …
complex tasks involved in wireless communications. Supported by recent advances in …
Deep learning for launching and mitigating wireless jamming attacks
An adversarial machine learning approach is introduced to launch jamming attacks on
wireless communications and a defense strategy is presented. A cognitive transmitter uses a …
wireless communications and a defense strategy is presented. A cognitive transmitter uses a …
Deep learning for wireless communications
Existing communication systems exhibit inherent limitations in translating theory to practice
when handling the complexity of optimization for emerging wireless applications with high …
when handling the complexity of optimization for emerging wireless applications with high …
Activethief: Model extraction using active learning and unannotated public data
Abstract Machine learning models are increasingly being deployed in practice. Machine
Learning as a Service (MLaaS) providers expose such models to queries by third-party …
Learning as a Service (MLaaS) providers expose such models to queries by third-party …
IoT network security from the perspective of adversarial deep learning
Machine learning finds rich applications in Internet of Things (IoT) networks such as
information retrieval, traffic management, spectrum sensing, and signal authentication. While …
information retrieval, traffic management, spectrum sensing, and signal authentication. While …
Adversarial deep learning for over-the-air spectrum poisoning attacks
An adversarial deep learning approach is presented to launch over-the-air spectrum
poisoning attacks. A transmitter applies deep learning on its spectrum sensing results to …
poisoning attacks. A transmitter applies deep learning on its spectrum sensing results to …
Adversarial machine learning for 5G communications security
Machine learning provides automated means to capture complex dynamics of wireless
spectrum and support better understanding of spectrum resources and their efficient …
spectrum and support better understanding of spectrum resources and their efficient …
Megex: Data-free model extraction attack against gradient-based explainable ai
T Miura, T Shibahara, N Yanai - Proceedings of the 2nd ACM Workshop …, 2024 - dl.acm.org
Explainable AI encourages machine learning applications in the real world, whereas data-
free model extraction attacks (DFME), in which an adversary steals a trained machine …
free model extraction attacks (DFME), in which an adversary steals a trained machine …
Attacks on machine learning: Adversarial examples in connected and autonomous vehicles
P Sharma, D Austin, H Liu - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Connected and autonomous vehicles (CAV aka driverless cars) offset human response for
transportation infrastructure, enhancing traffic efficiency, travel leisure, and road safety …
transportation infrastructure, enhancing traffic efficiency, travel leisure, and road safety …