K-means and alternative clustering methods in modern power systems

SM Miraftabzadeh, CG Colombo, M Longo… - Ieee …, 2023 - ieeexplore.ieee.org
As power systems evolve by integrating renewable energy sources, distributed generation,
and electric vehicles, the complexity of managing these systems increases. With the …

A review on feature selection in mobile malware detection

A Feizollah, NB Anuar, R Salleh, AWA Wahab - Digital investigation, 2015 - Elsevier
The widespread use of mobile devices in comparison to personal computers has led to a
new era of information exchange. The purchase trends of personal computers have started …

MTH-IDS: A multitiered hybrid intrusion detection system for internet of vehicles

L Yang, A Moubayed, A Shami - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Modern vehicles, including connected vehicles and autonomous vehicles, nowadays
involve many electronic control units connected through intravehicle networks (IVNs) to …

Recurrent neural network model for IoT and networking malware threat detection

M Woźniak, J Siłka, M Wieczorek… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Security of networking in cyber-physical systems is an important feature in recent computing.
Information that comes to the network needs preevaluation. Our solution presented in this …

Constructing features for detecting android malicious applications: issues, taxonomy and directions

W Wang, M Zhao, Z Gao, G Xu, H **an, Y Li… - IEEE …, 2019 - ieeexplore.ieee.org
The number of applications (apps) available for smart devices or Android based IoT (Internet
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …

A three-step machine learning framework for energy profiling, activity state prediction and production estimation in smart process manufacturing

D Tan, M Suvarna, YS Tan, J Li, X Wang - Applied Energy, 2021 - Elsevier
The dynamic nature of chemical processes and manufacturing environments, along with
numerous machines, their unique activity states, and mutual interactions, render challenges …

Malicious application detection in android—a systematic literature review

T Sharma, D Rattan - Computer Science Review, 2021 - Elsevier
Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …

[BOK][B] Machine learning approaches in cyber security analytics

T Thomas, AP Vijayaraghavan, S Emmanuel - 2019 - Springer
This book introduces various machine learning methods for cyber security analytics. With an
overwhelming amount of data being generated and transferred over various networks …

Hms-ids: Threat intelligence integration for zero-day exploits and advanced persistent threats in iiot

K Saurabh, V Sharma, U Singh, R Khondoker… - Arabian Journal for …, 2025 - Springer
Abstract Critical Industries such as Manufacturing, Power, and Intelligent Transportation are
increasingly using IIoT systems, making them more susceptible to cyberattacks. To counter …

An end-to-end lower limb activity recognition framework based on sEMG data augmentation and enhanced CapsNet

C Zhang, Y Li, Z Yu, X Huang, J Xu, C Deng - Expert Systems with …, 2023 - Elsevier
Recently, lower limb activity recognition (LLAR) based on surface electromyography (sEMG)
signal has attracted increasing attention, mainly due to its applications in the control of …