A lightweight supervised intrusion detection mechanism for IoT networks

2022 ◽  
Vol 127 ◽  
pp. 276-285
Author(s):  
Souradip Roy ◽  
Juan Li ◽  
Bong-Jin Choi ◽  
Yan Bai
2010 ◽  
Vol 29 (8) ◽  
pp. 859-874 ◽  
Author(s):  
Ioanna Kantzavelou ◽  
Sokratis Katsikas

The distributed computing is the buzz in recent past, cloud computing stands first in this category. This is since, the users can adapt anything related to data storage, magnificent computing facilities on a system with less infrastructure from anywhere at any time. On other dimension such public and private cloud computing strategies would also attracts the foul players to perform intrusion practices. This is since, the comfortability that the cloud platform providing to end users intends them to adapt these services in regard to save or compute the sensitive data. The scope of vulnerability to breach the data or services over cloud computing is more frequent and easier, which is since, these services relies on internet protocol. In this regard, the research in intrusion detection defense mechanisms is having prominent scope. This manuscript, projecting a novel intrusion detection mechanism called "calibration factors-based intrusion detection (CFID)" for cloud computing networks. The experimental study portrayed the significant scope of the proposal CFID to detect the intrusion activities listed as remoteto-Local, Port Scanning, and Virtual-Machine-Trapping.


Author(s):  
Sudarshan Nandy ◽  
Mainak Adhikari ◽  
Mohammad Ayoub Khan ◽  
Varun G Menon ◽  
Sandeep Verma

2020 ◽  
Vol 97 ◽  
pp. 101984 ◽  
Author(s):  
Dongzi Jin ◽  
Yiqin Lu ◽  
Jiancheng Qin ◽  
Zhe Cheng ◽  
Zhongshu Mao

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Abdulfattah Noorwali ◽  
Ahmad Naseem Alvi ◽  
Mohammad Zubair Khan ◽  
Muhammad Awais Javed ◽  
Wadii Boulila ◽  
...  

Wireless sensor network (WSN) is an integral part of Internet of Things (IoT). The sensor nodes in WSN generate large sensing data which is disseminated to intelligent servers using multiple wireless networks. This large data is prone to attacks from malicious nodes which become part of the network, and it is difficult to find these adversaries. The work in this paper presents a mechanism to detect adversaries for the IEEE 802.15.4 standard which is a central medium access protocol used in WSN-based IoT applications. The collisions and exhaustion attacks are detected based on a soft decision-based algorithm. In case the QoS of the network is compromised due to large data traffic, the proposed protocol adaptively varies the duty cycle of the IEEE 802.15.4. Simulation results show that the proposed intrusion detection and adaptive duty cycle algorithm improves the energy efficiency of a WSN with a reduced network delay.


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