Network intrusion detection for IoT security based on learning techniques
Pervasive growth of Internet of Things (IoT) is visible across the globe. The 2016 Dyn
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
cyberattack exposed the critical fault-lines among smart networks. Security of IoT has …
A Comprehensive Survey on Machine Learning‐Based Intrusion Detection Systems for Secure Communication in Internet of Things
SVN Santhosh Kumar, M Selvi… - Computational …, 2023 - Wiley Online Library
The Internet of Things (IoT) is a distributed system which is made up of the connections of
smart objects (things) that can continuously sense the events in their sensing domain and …
smart objects (things) that can continuously sense the events in their sensing domain and …
Intelligent approaches toward intrusion detection systems for Industrial Internet of Things: A systematic comprehensive review
M Nuaimi, LC Fourati, BB Hamed - Journal of Network and Computer …, 2023 - Elsevier
Recently years, we have seen the exponential upgrowth of the Industrial Internet of Things
(IIoT), which brings significant benefits to our daily lives, industry, and society. The common …
(IIoT), which brings significant benefits to our daily lives, industry, and society. The common …
Intrusion detection by machine learning: A review
CF Tsai, YF Hsu, CY Lin, WY Lin - expert systems with applications, 2009 - Elsevier
The popularity of using Internet contains some risks of network attacks. Intrusion detection is
one major research problem in network security, whose aim is to identify unusual access or …
one major research problem in network security, whose aim is to identify unusual access or …
Decision tree based light weight intrusion detection using a wrapper approach
The objective of this paper is to construct a lightweight Intrusion Detection System (IDS)
aimed at detecting anomalies in networks. The crucial part of building lightweight IDS …
aimed at detecting anomalies in networks. The crucial part of building lightweight IDS …
A two-level hybrid approach for intrusion detection
C Guo, Y Ping, N Liu, SS Luo - Neurocomputing, 2016 - Elsevier
To exploit the strengths of misuse detection and anomaly detection, an intensive focus on
intrusion detection combines the two. From a novel perspective, in this paper, we proposed …
intrusion detection combines the two. From a novel perspective, in this paper, we proposed …
A hierarchical intrusion detection model based on the PCA neural networks
Most of existing intrusion detection (ID) models with a single-level structure can only detect
either misuse or anomaly attacks. A hierarchical ID model using principal component …
either misuse or anomaly attacks. A hierarchical ID model using principal component …
[PDF][PDF] Survey on intrusion detection system using machine learning techniques
In today's world, almost everybody is affluent with computers and network based technology
is growing by leaps and bounds. So, network security has become very important, rather an …
is growing by leaps and bounds. So, network security has become very important, rather an …
Web intrusion detection system combined with feature analysis and SVM optimization
C Liu, J Yang, J Wu - EURASIP Journal on Wireless Communications and …, 2020 - Springer
The current network traffic is large, and the network attacks have multiple types. Therefore,
anomaly detection model combined with machine learning is developing rapidly. Frequent …
anomaly detection model combined with machine learning is developing rapidly. Frequent …
Real-time hybrid intrusion detection system using machine learning techniques
Intrusion and intrusive activities have become a bottleneck for both Internet and Intranet
users. An intrusion detection system tries to take care of such activities by constantly …
users. An intrusion detection system tries to take care of such activities by constantly …