[HTML][HTML] Res-TranBiLSTM: An intelligent approach for intrusion detection in the Internet of Things

S Wang, W Xu, Y Liu - Computer Networks, 2023 - Elsevier
Abstract The Internet of Things (IoT), as the information carrier of the Internet and
telecommunications networks, is a new network technology comprising physical entities …

Breaking alert fatigue: AI-assisted SIEM framework for effective incident response

T Ban, T Takahashi, S Ndichu, D Inoue - Applied Sciences, 2023 - mdpi.com
Contemporary security information and event management (SIEM) solutions struggle to
identify critical security incidents effectively due to the overwhelming number of false alerts …

An intrusion detection system for edge-envisioned smart agriculture in extreme environment

D Javeed, T Gao, MS Saeed… - IEEE internet of things …, 2023 - ieeexplore.ieee.org
The deployment of Internet of Things (IoT) systems in smart agriculture (SA) operates in
extreme environments, including wind, snowfall, flooding, landscape, and so on for …

Intrusion detection system for wireless sensor networks: A machine learning based approach

H Sadia, S Farhan, YU Haq, R Sana, T Mahmood… - IEEE …, 2024 - ieeexplore.ieee.org
In this era, plenty of wireless devices are being used with the support of WI-FI (Wireless
Fidelity) and need to be maintained and authorized. Wireless Sensor Networks (WSN), a …

Study on empowering cyber security by using Adaptive Machine Learning Methods

H Gonaygunta, GS Nadella, PP Pawar… - 2024 Systems and …, 2024 - ieeexplore.ieee.org
Machine Learning (ML) is pivotal in enhancing cybersecurity solutions, surpassing rule-
based methods. The complexity of modern malware demands robust detection systems …

[HTML][HTML] A comparative assessment of machine learning algorithms in the IoT-based network intrusion detection systems

M Samantaray, RC Barik, AK Biswal - Decision Analytics Journal, 2024 - Elsevier
The rapid increase in online risks is a reflection of the exponential growth of Internet of
Things (IoT) networks. Researchers have proposed numerous intrusion detection …

Team Work Optimizer Based Bidirectional LSTM Model for Designing a Secure Cybersecurity Model

R Vallabhaneni, HS Nagamani… - 2024 International …, 2024 - ieeexplore.ieee.org
The Internet's rapid growth and the volume of data being transmitted over it have been
accompanied by a steady increase in threats to network security. Hackers attempt to steal …

[HTML][HTML] Improved sand cat swarm optimization with deep learning based enhanced malicious activity recognition for cybersecurity

N Almakayeel, EL Lydia - Alexandria Engineering Journal, 2024 - Elsevier
The main concept of a smart city is to join manual items with electronics, software, sensors,
and network connectivity for data contact via Internet of Things (IoT) gadgets. IoT improves …

Advancing IoT security: a comprehensive AI-based trust framework for intrusion detection

CP Kaliappan, K Palaniappan… - Peer-to-Peer Networking …, 2024 - Springer
Over the years, the Internet of Things (IoT) devices have shown rapid proliferation and
development in various domains. However, the widespread adoption of smart devices …

Arp spoofing detection using machine learning classifiers: an experimental study

S Majumder, MK Deb Barma, A Saha - Knowledge and Information …, 2025 - Springer
Recent university data breaches highlight the need to protect sensitive information and
enhance centralized security systems like Software-Defined Networking and Intrusion …