A review of intrusion detection systems using machine and deep learning in internet of things: Challenges, solutions and future directions
The Internet of Things (IoT) is poised to impact several aspects of our lives with its fast
proliferation in many areas such as wearable devices, smart sensors and home appliances …
proliferation in many areas such as wearable devices, smart sensors and home appliances …
A holistic review of network anomaly detection systems: A comprehensive survey
N Moustafa, J Hu, J Slay - Journal of Network and Computer Applications, 2019 - Elsevier
Abstract Network Anomaly Detection Systems (NADSs) are gaining a more important role in
most network defense systems for detecting and preventing potential threats. The paper …
most network defense systems for detecting and preventing potential threats. The paper …
Towards the development of realistic botnet dataset in the internet of things for network forensic analytics: Bot-iot dataset
The proliferation of IoT systems, has seen them targeted by malicious third parties. To
address this challenge, realistic protection and investigation countermeasures, such as …
address this challenge, realistic protection and investigation countermeasures, such as …
A deep blockchain framework-enabled collaborative intrusion detection for protecting IoT and cloud networks
There has been significant research in incorporating both blockchain and intrusion detection
to improve data privacy and detect existing and emerging cyberattacks, respectively. In …
to improve data privacy and detect existing and emerging cyberattacks, respectively. In …
Novel deep learning-enabled LSTM autoencoder architecture for discovering anomalous events from intelligent transportation systems
Intelligent Transportation Systems (ITS), especially Autonomous Vehicles (AVs), are
vulnerable to security and safety issues that threaten the lives of the people. Unlike manual …
vulnerable to security and safety issues that threaten the lives of the people. Unlike manual …
Adaptive deep learning-based air quality prediction model using the most relevant spatial-temporal relations
Air pollution has become an extremely serious problem, with particulate matter having a
significantly greater impact on human health than other contaminants. The small diameter of …
significantly greater impact on human health than other contaminants. The small diameter of …
Enhancing IIoT networks protection: A robust security model for attack detection in Internet Industrial Control Systems
Abstract Industrial Internet of Things (IIoT) networks involves heterogeneous technological
and manufacturing services and devices. The communication and data exchange …
and manufacturing services and devices. The communication and data exchange …
An enhanced multi-stage deep learning framework for detecting malicious activities from autonomous vehicles
IA Khan, N Moustafa, D Pi, W Haider… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITS), particularly Autonomous Vehicles (AVs), are
susceptible to safety and security concerns that impend people's lives. Nothing like manually …
susceptible to safety and security concerns that impend people's lives. Nothing like manually …
Federated TON_IoT Windows datasets for evaluating AI-based security applications
N Moustafa, M Keshky, E Debiez… - 2020 IEEE 19th …, 2020 - ieeexplore.ieee.org
Existing cyber security solutions have been basically developed using knowledge-based
models that often cannot trigger new cyber-attack families. With the boom of Artificial …
models that often cannot trigger new cyber-attack families. With the boom of Artificial …
Outlier dirichlet mixture mechanism: Adversarial statistical learning for anomaly detection in the fog
Current anomaly detection systems (ADSs) apply statistical and machine learning
algorithms to discover zero-day attacks, but such algorithms are vulnerable to advanced …
algorithms to discover zero-day attacks, but such algorithms are vulnerable to advanced …