Edge computing technology enablers: A systematic lecture study
With the increasing stringent QoS constraints (eg, latency, bandwidth, jitter) imposed by
novel applications (eg, e-Health, autonomous vehicles, smart cities, etc.), as well as the …
novel applications (eg, e-Health, autonomous vehicles, smart cities, etc.), as well as the …
Transformers: A Security Perspective
The Transformers architecture has recently emerged as a revolutionary paradigm in the field
of deep learning, particularly excelling in Natural Language Processing (NLP) and …
of deep learning, particularly excelling in Natural Language Processing (NLP) and …
Adversarial attacks on machine learning in embedded and iot platforms
C Westbrook, S Pasricha - arXiv preprint arXiv:2303.02214, 2023 - arxiv.org
Machine learning (ML) algorithms are increasingly being integrated into embedded and IoT
systems that surround us, and they are vulnerable to adversarial attacks. The deployment of …
systems that surround us, and they are vulnerable to adversarial attacks. The deployment of …
Hybrid KD-NFT: A multi-layered NFT assisted robust Knowledge Distillation framework for Internet of Things
Abstract The Internet of Things (IoT) concept has increasingly gained popularity among
different industrial and scientific fields by leveraging the development of modern electronic …
different industrial and scientific fields by leveraging the development of modern electronic …
Split Edge-Cloud Neural Networks For Better Adversarial Robustness
Cloud computing is a critical component in the success of 5G and 6G networks, particularly
given the computation-intensive nature of emerging applications. Despite all it advantages …
given the computation-intensive nature of emerging applications. Despite all it advantages …
Detection of Adversarial Attacks by Observing Deep Features with Structured Data Algorithms
Deep Neural Networks (DNNs) are highly vulnerable to adversarial attacks, which introduce
human-imperceptible perturbations on the input to fool a DNN model. Detecting such attacks …
human-imperceptible perturbations on the input to fool a DNN model. Detecting such attacks …
A Robust NFT Assisted Knowledge Distillation Framework for Edge Computing
With the development and improvement in chip manufacturing and network communication,
Internet of Things (IoT) have been addressing more and more popularity around these days …
Internet of Things (IoT) have been addressing more and more popularity around these days …
EnsGuard: A Novel Acceleration Framework for Adversarial Ensemble Learning
To defend against various adversarial attacks, it is essential to develop a robust and high
computing efficiency defence framework. Adversarial ensemble learning is the most effective …
computing efficiency defence framework. Adversarial ensemble learning is the most effective …
Early Exists Federated Learning (EEFL): Brining Training to the Edge
With the proliferation of IoT devices, the core network is experiencing overwhelming
congestion. Edge Com-puting emerges as a valuable and promising solution to relocate …
congestion. Edge Com-puting emerges as a valuable and promising solution to relocate …
对抗训练驱动的恶意代码检测增强方法
为了解决恶意代码检测器对于对抗性输入检测能力的不足, 提出了一种对抗训练驱动的恶意代码
检测增强方法. 首先, 通过反编译工具对应用程序进行预处理, 提取应用程序接口(API) 调用特征 …
检测增强方法. 首先, 通过反编译工具对应用程序进行预处理, 提取应用程序接口(API) 调用特征 …