Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Machine and deep learning solutions for intrusion detection and prevention in IoTs: A survey
The increasing number of connected devices in the era of Internet of Thing (IoT) has also
increased the number intrusions. Intrusion Detection System (IDS) is a secondary intelligent …
increased the number intrusions. Intrusion Detection System (IDS) is a secondary intelligent …
Intrusion detection based on machine learning techniques in computer networks
Intrusions in computer networks have increased significantly in the last decade, due in part
to a profitable underground cyber-crime economy and the availability of sophisticated tools …
to a profitable underground cyber-crime economy and the availability of sophisticated tools …
A multi-objective mutation-based dynamic Harris Hawks optimization for botnet detection in IoT
The increasing trend toward using the Internet of Things (IoT) increased the number of
intrusions and intruders annually. Hence, the integration, confidentiality, and access to …
intrusions and intruders annually. Hence, the integration, confidentiality, and access to …
[PDF][PDF] Attack and anomaly detection in iot networks using machine learning techniques: A review
SH Haji, SY Ameen - Asian J. Res. Comput. Sci, 2021 - researchgate.net
ABSTRACT The Internet of Things (IoT) is one of today's most rapidly growing technologies.
It is a technology that allows billions of smart devices or objects known as" Things" to collect …
It is a technology that allows billions of smart devices or objects known as" Things" to collect …
MOAEOSCA: an enhanced multi-objective hybrid artificial ecosystem-based optimization with sine cosine algorithm for feature selection in botnet detection in IoT
The number of Internet of Things (IoT) devices overgrows, and this technology dominates.
The importance of IoT security and the growing need to devise intrusion detection systems …
The importance of IoT security and the growing need to devise intrusion detection systems …
An Ensemble‐Based Multiclass Classifier for Intrusion Detection Using Internet of Things
Internet of Things (IoT) is the fastest growing technology that has applications in various
domains such as healthcare, transportation. It interconnects trillions of smart devices through …
domains such as healthcare, transportation. It interconnects trillions of smart devices through …
Botnet attacks classification in AMI networks with recursive feature elimination (RFE) and machine learning algorithms
Abstract STRIDE (Spoofing, Tampering, Repudiation, Information Disclosure, Escalation of
privilege) in advance metering infrastructure (AMI) and cloud computing have been …
privilege) in advance metering infrastructure (AMI) and cloud computing have been …
Influence of statistical feature normalisation methods on K-Nearest Neighbours and K-Means in the context of industry 4.0
Normalisation is a preprocessing technique widely employed in Machine Learning (ML)-
based solutions for industry to equalise the features' contribution. However, few researchers …
based solutions for industry to equalise the features' contribution. However, few researchers …
[HTML][HTML] IoT multi-vector cyberattack detection based on machine learning algorithms: traffic features analysis, experiments, and efficiency
Cybersecurity is a common Internet of Things security challenge. The lack of security in IoT
devices has led to a great number of devices being compromised, with threats from both …
devices has led to a great number of devices being compromised, with threats from both …
ML techniques for attack and anomaly detection in internet of things networks
Summary The Internet of Things (IoT), is a fundamental driver of smart cities. It is the
champion of the global collaboration of machines/things, people, huge data, and processes …
champion of the global collaboration of machines/things, people, huge data, and processes …