A review on machine learning and deep learning perspectives of IDS for IoT: recent updates, security issues, and challenges
Abstract Internet of Things (IoT) is widely accepted technology in both industrial as well as
academic field. The objective of IoT is to combine the physical environment with the cyber …
academic field. The objective of IoT is to combine the physical environment with the cyber …
A survey of machine and deep learning methods for internet of things (IoT) security
The Internet of Things (IoT) integrates billions of smart devices that can communicate with
one another with minimal human intervention. IoT is one of the fastest developing fields in …
one another with minimal human intervention. IoT is one of the fastest developing fields in …
Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
Deep learning for side-channel analysis and introduction to ASCAD database
R Benadjila, E Prouff, R Strullu, E Cagli… - Journal of Cryptographic …, 2020 - Springer
Recent works have demonstrated that deep learning algorithms were efficient to conduct
security evaluations of embedded systems and had many advantages compared to the other …
security evaluations of embedded systems and had many advantages compared to the other …
How machine learning changes the nature of cyberattacks on IoT networks: A survey
The Internet of Things (IoT) has continued gaining in popularity and importance in everyday
life in recent years. However, this development does not only present advantages. Indeed …
life in recent years. However, this development does not only present advantages. Indeed …
Convolutional neural networks with data augmentation against jitter-based countermeasures: Profiling attacks without pre-processing
E Cagli, C Dumas, E Prouff - … and Embedded Systems–CHES 2017: 19th …, 2017 - Springer
In the context of the security evaluation of cryptographic implementations, profiling attacks
(aka Template Attacks) play a fundamental role. Nowadays the most popular Template …
(aka Template Attacks) play a fundamental role. Nowadays the most popular Template …
Sok: Deep learning-based physical side-channel analysis
Side-channel attacks represent a realistic and serious threat to the security of embedded
devices for already almost three decades. A variety of attacks and targets they can be …
devices for already almost three decades. A variety of attacks and targets they can be …
{CSI}{NN}: Reverse engineering of neural network architectures through electromagnetic side channel
Machine learning has become mainstream across industries. Numerous examples prove the
validity of it for security applications. In this work, we investigate how to reverse engineer a …
validity of it for security applications. In this work, we investigate how to reverse engineer a …
Make some noise. unleashing the power of convolutional neural networks for profiled side-channel analysis
Profiled side-channel analysis based on deep learning, and more precisely Convolutional
Neural Networks, is a paradigm showing significant potential. The results, although scarce …
Neural Networks, is a paradigm showing significant potential. The results, although scarce …
Non-profiled deep learning-based side-channel attacks with sensitivity analysis
B Timon - IACR Transactions on Cryptographic Hardware and …, 2019 - tches.iacr.org
Deep Learning has recently been introduced as a new alternative to perform Side-Channel
analysis [MPP16]. Until now, studies have been focused on applying Deep Learning …
analysis [MPP16]. Until now, studies have been focused on applying Deep Learning …