Artificial neural networks based optimization techniques: A review
In the last few years, intensive research has been done to enhance artificial intelligence (AI)
using optimization techniques. In this paper, we present an extensive review of artificial …
using optimization techniques. In this paper, we present an extensive review of artificial …
Task scheduling in cloud computing based on meta-heuristics: review, taxonomy, open challenges, and future trends
Cloud computing is a recently looming-evoked paradigm, the aim of which is to provide on-
demand, pay-as-you-go, internet-based access to shared computing resources (hardware …
demand, pay-as-you-go, internet-based access to shared computing resources (hardware …
Hybrid intrusion detection using mapreduce based black widow optimized convolutional long short-term memory neural networks
PR Kanna, P Santhi - Expert Systems with Applications, 2022 - Elsevier
The recent advancements in information and communication technologies have led to an
increasing number of online systems and services. These online systems can utilize …
increasing number of online systems and services. These online systems can utilize …
MQTTset, a new dataset for machine learning techniques on MQTT
IoT networks are increasingly popular nowadays to monitor critical environments of different
nature, significantly increasing the amount of data exchanged. Due to the huge number of …
nature, significantly increasing the amount of data exchanged. Due to the huge number of …
A survey on data-driven network intrusion detection
Data-driven network intrusion detection (NID) has a tendency towards minority attack
classes compared to normal traffic. Many datasets are collected in simulated environments …
classes compared to normal traffic. Many datasets are collected in simulated environments …
Computational intelligence intrusion detection techniques in mobile cloud computing environments: Review, taxonomy, and open research issues
S Shamshirband, M Fathi, AT Chronopoulos… - Journal of Information …, 2020 - Elsevier
With the increasing utilization of the Internet and its provided services, an increase in cyber-
attacks to exploit the information occurs. A technology to store and maintain user's …
attacks to exploit the information occurs. A technology to store and maintain user's …
Machine learning and deep learning methods for intrusion detection systems: recent developments and challenges
G Kocher, G Kumar - Soft Computing, 2021 - Springer
Deep learning (DL) is gaining significant prevalence in every field of study due to its
domination in training large data sets. However, several applications are utilizing machine …
domination in training large data sets. However, several applications are utilizing machine …
Hybrid approach to intrusion detection in fog-based IoT environments
CA De Souza, CB Westphall, RB Machado… - Computer Networks, 2020 - Elsevier
Abstract In the Internet of Things (IoT) systems, information of various kinds is continuously
captured, processed, and transmitted by systems generally interconnected by the Internet …
captured, processed, and transmitted by systems generally interconnected by the Internet …
Intrusion detection systems in the Internet of things: A comprehensive investigation
S Hajiheidari, K Wakil, M Badri, NJ Navimipour - Computer Networks, 2019 - Elsevier
Recently, a new dimension of intelligent objects has been provided by reducing the power
consumption of electrical appliances. Daily physical objects have been upgraded by …
consumption of electrical appliances. Daily physical objects have been upgraded by …
The future energy internet for utility energy service and demand-side management in smart grid: Current practices, challenges and future directions
The energy internet (EI) integrated with smart grid (SG) has been a growing and emerging
technology that manages and controls towards reliability, security, data integrity, demand …
technology that manages and controls towards reliability, security, data integrity, demand …