A survey of CNN-based network intrusion detection

L Mohammadpour, TC Ling, CS Liew, A Aryanfar - Applied Sciences, 2022 - mdpi.com
Over the past few years, Internet applications have become more advanced and widely
used. This has increased the need for Internet networks to be secured. Intrusion detection …

[HTML][HTML] Anomaly-based cyberattacks detection for smart homes: A systematic literature review

JII Araya, H Rifà-Pous - Internet of Things, 2023 - Elsevier
Smart homes, leveraging IoT technology to interconnect various devices and appliances to
the internet, enable remote monitoring, automation, and control. However, collecting …

A review on action recognition for accident detection in smart city transportation systems

VA Adewopo, N Elsayed, Z ElSayed, M Ozer… - Journal of Electrical …, 2023 - Springer
Accident detection and public traffic safety is a crucial aspect of safe and better community.
Monitoring traffic flow in smart cities using different surveillance cameras plays a crucial role …

BLoCNet: a hybrid, dataset-independent intrusion detection system using deep learning

B Bowen, A Chennamaneni, A Goulart… - International Journal of …, 2023 - Springer
Intrusion detection systems (IDS) identify cyber attacks given a sample of network traffic
collected from real-world computer networks. As a powerful classification tool, deep learning …

Intrusion detection model for IoT using recurrent kernel convolutional neural network

CU Om Kumar, S Marappan, B Murugeshan… - Wireless Personal …, 2023 - Springer
In communication and information technology, the Internet of Things (IoT) creates an
enormous amount of data traffic that permits data analysis to expose and detect unusual …

Smart home gateway based on integration of deep reinforcement learning and blockchain framework

Z Shahbazi, YC Byun, HY Kwak - Processes, 2021 - mdpi.com
The development of information and communication technology in terms of sensor
technologies cause the Internet of Things (IoT) step toward smart homes for prevalent …

A Network Intrusion Detection Model Based on BiLSTM with Multi-Head Attention Mechanism

J Zhang, X Zhang, Z Liu, F Fu, Y Jiao, F Xu - Electronics, 2023 - mdpi.com
A network intrusion detection tool can identify and detect potential malicious activities or
attacks by monitoring network traffic and system logs. The data within intrusion detection …

A hybrid deep learning approach for advanced persistent threat attack detection

M Alrehaili, A Alshamrani, A Eshmawi - Proceedings of the 5th …, 2021 - dl.acm.org
Advanced Persistent Threat (APT) attack is one of the most common and costly destructive
attacks on the target system. This attack has become a challenge for companies …

An enhancement method in few-shot scenarios for intrusion detection in smart home environments

Y Chen, J Wang, T Yang, Q Li, NA Nijhum - Electronics, 2023 - mdpi.com
Different devices in the smart home environment are subject to different levels of attack.
Devices with lower attack frequencies confront difficulties in collecting attack data, which …

Attack and Anomaly Detection in IIoT Networks Using Machine Learning Techniques

P Kumar, I Banerjee - 2023 14th International Conference on …, 2023 - ieeexplore.ieee.org
Sensor-driven edge devices, known as things, connect with control systems like intelligent
machines and analytic applications, making a network known as the Industrial Internet of …