Cluster-Based Intrusion Detection Method for Internet of Things

2019 ◽  
Author(s):  
Sarika Choudhary ◽  
Nishtha Kesswani
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Detection Method

scholarly journals An Automata Based Intrusion Detection Method for Internet of Things

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Yulong Fu ◽  
Zheng Yan ◽  
Jin Cao ◽  
Ousmane Koné ◽  
Xuefei Cao
Keyword(s):  
Open Access ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Detection Method ◽  
Detection System ◽  
Network Communication ◽  
5G Networks ◽  
Machine To Machine ◽  
Security Of Iot

Internet of Things (IoT) transforms network communication to Machine-to-Machine (M2M) basis and provides open access and new services to citizens and companies. It extends the border of Internet and will be developed as one part of the future 5G networks. However, as the resources of IoT’s front devices are constrained, many security mechanisms are hard to be implemented to protect the IoT networks. Intrusion detection system (IDS) is an efficient technique that can be used to detect the attackers when cryptography is broken, and it can be used to enforce the security of IoT networks. In this article, we analyzed the intrusion detection requirements of IoT networks and then proposed a uniform intrusion detection method for the vast heterogeneous IoT networks based on an automata model. The proposed method can detect and report the possible IoT attacks with three types: jam-attack, false-attack, and reply-attack automatically. We also design an experiment to verify the proposed IDS method and examine the attack of RADIUS application.

Research of IOT Intrusion Detection System Based on Hidden Markov Model

2012 ◽  
Vol 263-266 ◽  
pp. 2949-2952
Author(s):  
Xiu Mei Wei ◽  
Xue Song Jiang ◽  
Xin Gang Wang
Keyword(s):  
Time Delay ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Intrusion Detection System ◽  
Detection Method ◽  
Hidden Markov ◽  
Detection System ◽  
Markov State

Along with the development of Internet of Things (IOT), there are a lot of increasingly serious security problems. The traditional intrusion detection method cannot adapt to the requirement of IOT. In this paper we advance a new intrusion detection method which can adapt to IOT. It is based on Hidden Markov Model (HMM), which is named as Hidden Markov state time delay sequence embedding (HMMSTdse) method.

Research on Data Security Detection Algorithm in IoT Based on K-means

2021 ◽  
Vol 14 ◽  
Author(s):  
Jianxing Zhu ◽  
Lina Huo ◽  
Mohd Dilshad Ansari ◽  
Mohammad Asif Ikbal
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Data Security ◽  
Detection Method ◽  
Detection Algorithm ◽  
The Internet ◽  
Human Beings ◽  
Network Attacks ◽  
Hybrid Detection ◽  
The Internet Of Things

Background: The development of the Internet of Things has prominently expanded the perception of human beings, but ensuing security issues have attracted people's attention. From the perspective of the relatively weak sensor network in the Internet of Things. Method: Proposed method Aiming at the characteristics of diversification and heterogeneity of collected data in sensor networks, the data set is clustered and analyzed from the aspects of network delay and data flow to extract data characteristics. Then, according to the characteristics of different types of network attacks, a hybrid detection method for network attacks is established. An efficient data intrusion detection algorithm based on K-means clustering is proposed Results: This paper proposes a network node control method based on traffic constraints to improve the security level of the network. Simulation experiments show that compared with traditional password-based intrusion detection methods; the proposed method has a higher detection level and is suitable for data security protection in the Internet of Things. Conclusions: This paper proposes an efficient intrusion detection method for applications with Internet of Things

scholarly journals Research on Data Security Detection Algorithm in IoT Based on K-means

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Jianxing Zhu ◽  
Lina Huo ◽  
Mohd Dilshad Ansari ◽  
Mohammad Asif Ikbal
Keyword(s):  
Internet Of Things ◽  
Intrusion Detection ◽  
Data Security ◽  
Detection Method ◽  
Detection Algorithm ◽  
The Internet ◽  
Human Beings ◽  
Network Attacks ◽  
Hybrid Detection ◽  
The Internet Of Things

The development of the Internet of Things has prominently expanded the perception of human beings, but ensuing security issues have attracted people's attention. From the perspective of the relatively weak sensor network in the Internet of Things. Proposed method is aiming at the characteristics of diversification and heterogeneity of collected data in sensor networks; the data set is clustered and analyzed from the aspects of network delay and data flow to extract data characteristics. Then, according to the characteristics of different types of network attacks, a hybrid detection method for network attacks is established. An efficient data intrusion detection algorithm based on K-means clustering is proposed. This paper proposes a network node control method based on traffic constraints to improve the security level of the network. Simulation experiments show that compared with traditional password-based intrusion detection methods; the proposed method has a higher detection level and is suitable for data security protection in the Internet of Things. This paper proposes an efficient intrusion detection method for applications with Internet of Things.

scholarly journals Intrusion Detection Analysis of Internet of Things considering Practical Byzantine Fault Tolerance (PBFT) Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Leixia Li ◽  
Yong Chen ◽  
Baojun Lin
Keyword(s):  
Fault Tolerance ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Detection Method ◽  
Detection Methods ◽  
The Internet ◽  
Byzantine Fault Tolerance ◽  
Byzantine Fault ◽  
Operation Process ◽  
The Internet Of Things

In order to improve the security performance and accuracy of the Internet of things in the use process, it is necessary to use the Internet of things intrusion detection method. At present, the problem of inconsistency between the accuracy of detection results and nodes is more prominent when the Internet of things intrusion detection methods are running. This paper proposes a practical Byzantine fault-tolerant intrusion detection method for the use process of the Internet of things. This method introduces the intrusion detection method and the operation function of foreign attackers on the basis of practical Byzantine fault tolerance; using the expected utility function to the corresponding benefit function of practical Byzantine fault tolerance, the results of Internet of things intrusion detection model can be effectively calculated. Finally, the experimental results show that compared with the existing intrusion detection methods, the proposed method can effectively reduce the energy consumption of the Internet of things in the operation process, can effectively reduce 14.3% and 7.8%, and can effectively reduce the energy consumption of the Internet of things in the operation process.

A Novel Intrusion Detection Method Based on Lightweight Neural Network for Internet of Things

2021 ◽  
pp. 1-1
Author(s):  
Ruijie Zhao ◽  
Guan Gui ◽  
Zhi Xue ◽  
Jie Yin ◽  
Tomoaki Ohtsuki ◽  
...  
Keyword(s):  
Neural Network ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Detection Method
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