Experts and intelligent systems for smart homes' Transformation to Sustainable Smart Cities: A comprehensive review

NU Huda, I Ahmed, M Adnan, M Ali, F Naeem - Expert Systems with …, 2024 - Elsevier
In this constantly evolving landscape of urbanization, the relationship between technology
and automation, in regards to sustainability, holds immense significance. The intricate …

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security

S Shitharth, AM Alshareef, AO Khadidos, KH Alyoubi… - Scientific Reports, 2023 - nature.com
Ensuring the privacy and trustworthiness of smart city—Internet of Things (IoT) networks
have recently remained the central problem. Cyborg intelligence is one of the most popular …

Android malware detection as a bi-level problem

M Jerbi, ZC Dagdia, S Bechikh, LB Said - Computers & Security, 2022 - Elsevier
Malware detection is still a very challenging topic in the cybersecurity field. This is mainly
due to the use of obfuscation techniques. To solve this issue, researchers proposed to …

Design of advanced intrusion detection systems based on hybrid machine learning techniques in hierarchically wireless sensor networks

GG Gebremariam, J Panda, S Indu - Connection Science, 2023 - Taylor & Francis
Wireless sensor networks (WSNs) are an emerging military and civilian technology that uses
sensors. Sensor networks are hierarchical and chaotic in remote, unmonitored sites …

[PDF][PDF] Privacy Preserving Blockchain with Optimal Deep Learning Model for Smart Cities.

K Kumar, J Mahilraj, D Swathi… - … , Materials & Continua, 2022 - academia.edu
Recently, smart cities have emerged as an effective approach to deliver high-quality
services to the people through adaptive optimization of the available resources. Despite the …

Network intrusion detection and mitigation in SDN using deep learning models

M Maddu, YN Rao - International Journal of Information Security, 2024 - Springer
Abstract Software-Defined Networking (SDN) is a contemporary network strategy utilized
instead of a traditional network structure. It provides significantly more administrative …

A novel hybrid autoencoder and modified particle swarm optimization feature selection for intrusion detection in the internet of things network

YK Saheed, AA Usman, FD Sukat… - Frontiers in Computer …, 2023 - frontiersin.org
The Internet of Things (IoT) represents a paradigm shift in which the Internet is connected to
real objects in a range of areas, including home automation, industrial processes, human …

MAC Protocol Based IoT Network Intrusion Detection Using Improved Efficient Shuffle Bidirectional COOT Channel Attention Network

NKS Nayak, B Bhattacharyya - IEEE Access, 2023 - ieeexplore.ieee.org
The IoT networks are customized to work under various smart environments, utilizing diverse
sensors. However, they are vulnerable to several cyberattacks because of their finite …

[PDF][PDF] Strengthening Network Security: Deep Learning Models for Intrusion Detection with Optimized Feature Subset and Effective Imbalance Handling

B Xu, L Sun, X Mao, C Liu, Z Ding - Computers, Materials & …, 2024 - cdn.techscience.cn
In recent years, frequent network attacks have highlighted the importance of efficient
detection methods for ensuring cyberspace security. This paper presents a novel intrusion …

An Improved Deep Learning Model for Electricity Price Forecasting

R Iqbal, H Mokhlis, AS Mohd Khairuddin… - 2023 - reunir.unir.net
Accurate electricity price forecasting (EPF) is important for the purpose of bidding strategies
and minimizing the risk for market participants in the competitive electricity market. Besides …