Network intrusion detection system: A systematic study of machine learning and deep learning approaches
The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …
increase in the network size and the corresponding data. As a result, many novel attacks are …
A critical review of intrusion detection systems in the internet of things: techniques, deployment strategy, validation strategy, attacks, public datasets and challenges
A Khraisat, A Alazab - Cybersecurity, 2021 - Springer
Abstract The Internet of Things (IoT) has been rapidly evolving towards making a greater
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
impact on everyday life to large industrial systems. Unfortunately, this has attracted the …
[HTML][HTML] A machine learning-based intrusion detection for detecting internet of things network attacks
Abstract The Internet of Things (IoT) refers to the collection of all those devices that could
connect to the Internet to collect and share data. The introduction of varied devices …
connect to the Internet to collect and share data. The introduction of varied devices …
PPSF: A privacy-preserving and secure framework using blockchain-based machine-learning for IoT-driven smart cities
With the evolution of the Internet of Things (IoT), smart cities have become the mainstream of
urbanization. IoT networks allow distributed smart devices to collect and process data within …
urbanization. IoT networks allow distributed smart devices to collect and process data within …
A survey on machine learning techniques for cyber security in the last decade
Pervasive growth and usage of the Internet and mobile applications have expanded
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
cyberspace. The cyberspace has become more vulnerable to automated and prolonged …
Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study
In this paper, we present a survey of deep learning approaches for cyber security intrusion
detection, the datasets used, and a comparative study. Specifically, we provide a review of …
detection, the datasets used, and a comparative study. Specifically, we provide a review of …
Construction 4.0: A literature review
The construction industry is experiencing changes in its processes and work methods, and
the advancement of new technologies in recent decades has led to a new concept known as …
the advancement of new technologies in recent decades has led to a new concept known as …
Human action recognition using attention based LSTM network with dilated CNN features
Human action recognition in videos is an active area of research in computer vision and
pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for …
pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for …
[HTML][HTML] Towards a machine learning-based framework for DDOS attack detection in software-defined IoT (SD-IoT) networks
Abstract The Internet of Things (IoT) is a complex and diverse network consisting of resource-
constrained sensors/devices/things that are vulnerable to various security threats …
constrained sensors/devices/things that are vulnerable to various security threats …
Explainable artificial intelligence (XAI) to enhance trust management in intrusion detection systems using decision tree model
Despite the growing popularity of machine learning models in the cyber‐security
applications (eg, an intrusion detection system (IDS)), most of these models are perceived …
applications (eg, an intrusion detection system (IDS)), most of these models are perceived …