Machine learning solutions for mobile internet of things security: A literature review and research agenda

H Messabih, CA Kerrache… - Transactions on …, 2024 - Wiley Online Library
In recent years, the advancements in wireless technologies and sensor networks have
promoted the Mobile Internet of Things (MIoT) paradigm. However, the unique …

Research on adaptive 1DCNN network intrusion detection technology based on BSGM mixed sampling

W Ma, C Gou, Y Hou - Sensors, 2023 - mdpi.com
The development of internet technology has brought us benefits, but at the same time, there
has been a surge in network attack incidents, posing a serious threat to network security. In …

[HTML][HTML] Enhancing soil organic carbon prediction of LUCAS soil database using deep learning and deep feature selection

M Saberioon, A Gholizadeh, A Ghaznavi… - … and Electronics in …, 2024 - Elsevier
The main terrestrial carbon (C) fraction is soil organic carbon (SOC), which has a
considerable effect on climate change and greenhouse gas emissions through the …

Multi-view consistent generative adversarial network for enhancing intrusion detection with prevention systems in mobile ad hoc networks against security attacks

M Rajkumar, J Karthika - Computers & Security, 2025 - Elsevier
Abstract Improving security in Mobile Ad hoc Networks (MANETs) requires an effective
intrusion detection and prevention scheme that addresses some research issues, such as …

APSO-CNN-SE: An Adaptive Convolutional Neural Network Approach for IoT Intrusion Detection.

Y Ban, D Zhang, Q He, Q Shen - Computers, Materials & …, 2024 - search.ebscohost.com
The surge in connected devices and massive data aggregation has expanded the scale of
the Internet of Things (IoT) networks. The proliferation of unknown attacks and related risks …

Analysis of Encrypted Network Traffic for Enhancing Cyber-security in Dynamic Environments

F Alserhani - Applied Artificial Intelligence, 2024 - Taylor & Francis
At present, encrypted data is the cornerstone of Internet communication, providing the
maximum degree of privacy and security protection for all transmitted data while shielding …

Exploring Machine learning algorithms for Malicious node detection using cluster based trust entropy

S Kanthimathi - IEEE Access, 2024 - ieeexplore.ieee.org
Machine learning has, over the decades, ushered in a dramatic transformation across a
range of sectors, including network security. Security experts agree that the potential of …

RETRACTED ARTICLE: Analyzing the impacts of node density and speed on routing protocol performance in firefighting applications

I Ullah, T Hussain, A Khan, I Ali, F Ali, C Choi - Fire Ecology, 2023 - Springer
Background Mobile ad hoc networks have piqued researchers' interest in various
applications, including forest fire detection. Because of the massive losses caused by this …

Multicast On-Route cluster propagation to detect network intrusion detection systems on MANET using Deep Operator Neural networks

K Saminathan, L Perumal, FH Sha**… - Expert Systems with …, 2024 - Elsevier
Abstract Mobile Ad-hoc Networks (MANETs) face significant challenges related to security
threats and energy efficiency due to their dynamic nature. Traditional approaches have …

Adaptive Marine Predator Optimization Algorithm (AOMA)-Deep Supervised Learning Classification (DSLC) Based IDS Framework for MANET Security

MS Sheela, AG Soundari, A Mudigonda… - Intelligent and …, 2024 - ieeexplore.ieee.org
Due to the dynamic nature and node mobility, assuring the security of Mobile Ad-hoc
Networks (MANET) is one of the difficult and challenging tasks today. In MANET, the …