Mitigating denial of service attacks in RPL-based IoT environments: trust-based approach

F Azzedin - IEEE Access, 2023 - ieeexplore.ieee.org
In domains such as telehealth, intelligent transportation, and autonomous agriculture,
ensuring secure routing of collected and exchanged data is paramount. Since its inception …

Deep Learning for Intrusion Detection Systems (IDSs) in Time Series Data

K Psychogyios, A Papadakis, S Bourou, N Nikolaou… - Future Internet, 2024 - mdpi.com
The advent of computer networks and the internet has drastically altered the means by
which we share information and interact with each other. However, this technological …

Data driven intrusion detection for 6LoWPAN based IoT systems

FK Örs, A Levi - Ad Hoc Networks, 2023 - Elsevier
Wide adoption of Internet of Things (IoT) devices and their limitations in terms of hardware
cause them to be easy targets for attackers. This, in turn, requires monitoring such systems …

Dair-mlt: detection and avoidance of IoT routing attacks using machine learning techniques

D Paganraj - International Journal of Information Technology, 2024 - Springer
Abstract The Internet of Things (IoT) aims to increase the physical device's intelligence.
These devices are capable of exchanging data without human intervention. But, IoT devices …

[HTML][HTML] LETM-IoT: A lightweight and efficient trust mechanism for Sybil attacks in Internet of Things networks

J Hassan, A Sohail, AI Awad, MA Zaka - Ad Hoc Networks, 2024 - Elsevier
Abstract The Internet of Things (IoT) has recently gained significance as a means of
connecting various physical devices to the Internet, enabling various innovative …

OPSMOTE-ML: an optimized SMOTE with machine learning models for selective forwarding attack detection in low power and lossy networks of internet of things

TA Al-Amiedy, M Anbar, B Belaton - Cluster Computing, 2024 - Springer
Abstract The Internet of Things represents a rapidly evolving networking paradigm that
brings numerous benefits through its diverse applications. Advances in embedded system …

Prediction of pedestrian crossing behaviour at unsignalized intersections using machine learning algorithms: analysis and comparison

D Singh, P Das, I Ghosh - Journal on Multimodal User Interfaces, 2024 - Springer
The primary safety hazard at unsignalized intersections, particularly in urban areas, is
pedestrian-vehicle collisions. Due to its complexity and inattention, pedestrian crossing …

Graph-ensemble fusion for enhanced IoT intrusion detection: leveraging GCN and deep learning

K Mittal, P Khurana Batra - Cluster Computing, 2024 - Springer
The proliferation of Internet of Things (IoT) applications has heightened the vulnerability of
information security, making it susceptible to attacks that may lead to the compromise of …

[PDF][PDF] Routing attack detection using ensemble deep learning model for IIoT

R Vatambeti, G Mamidisetti - Inf. Dyn. Appl, 2023 - library.acadlore.com
Smart cities, ITS, supply chains, and smart industries may all be developed with minimal
human interaction thanks to the increasing prevalence of automation enabled by machine …

Intelligent Detecting of Emergency Vehicles on the Road Networks: Available Datasets Assessment

M Shatnawi, MB Younes - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Intelligent transport systems have received high attention from researchers as part of smart
cities recently. Several advanced technologies have been used to enhance the smart …