scholarly journals Dynamic Access Control Policy based on Blockchain and Machine Learning for the Internet of Things

2017 ◽  
Vol 8 (7) ◽  
Author(s):  
Aissam OUTCHAKOUCHT ◽  
Hamza ES-SAMAALI ◽  
Jean Philippe
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Access Control ◽  
Control Policy ◽  
The Internet ◽  
Access Control Policy ◽  
The Internet Of Things ◽  
Dynamic Access Control

scholarly journals Secure and dynamic access control for the Internet of Things (IoT) based traffic system

2021 ◽  
Vol 7 ◽  
pp. e471
Author(s):  
Muhammad Umar Aftab ◽  
Ariyo Oluwasanmi ◽  
Abdullah Alharbi ◽  
Osama Sohaib ◽  
Xuyun Nie ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Access Control ◽  
Traffic Control ◽  
Vehicular Networks ◽  
Smart Devices ◽  
The Internet ◽  
Proposed Model ◽  
Parking Management ◽  
The Internet Of Things ◽  
Dynamic Access Control

Today, the trend of the Internet of Things (IoT) is increasing through the use of smart devices, vehicular networks, and household devices with internet-based networks. Specifically, the IoT smart devices and gadgets used in government and military are crucial to operational success. Communication and data sharing between these devices have increased in several ways. Similarly, the threats of information breaches between communication channels have also surged significantly, making data security a challenging task. In this context, access control is an approach that can secure data by restricting unauthorized users. Various access control models exist that can effectively implement access control yet, and there is no single state-of-the-art model that can provide dynamicity, security, ease of administration, and rapid execution all at once. In combating this loophole, we propose a novel secure and dynamic access control (SDAC) model for the IoT networks (smart traffic control and roadside parking management). Our proposed model allows IoT devices to communicate and share information through a secure means by using wired and wireless networks (Cellular Networks or Wi-Fi). The effectiveness and efficiency of the proposed model are demonstrated using mathematical models and discussed with many example implementations.

Detecting Abnormal Behavior of an IoT Device in the Network Based on a Traffic Model

Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Mobile Networks ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Abnormal Behavior ◽  
Traffic Model ◽  
The Internet ◽  
Wide Spread ◽  
The Internet Of Things

The article deals with the СoAP Protocol that regulates the transmission and reception of information traf-fic by terminal devices in IoT networks. The article describes a model for detecting abnormal traffic in 5G/IoT networks using machine learning algorithms, as well as the main methods for solving this prob-lem. The relevance of the article is due to the wide spread of the Internet of things and the upcoming update of mobile networks to the 5g generation.

scholarly journals IMPROVING INTERNET OF THINGS PARKING SYSTEMS

2021 ◽  
Vol 19 (3) ◽  
pp. 163
Author(s):  
Dušan Bogićević
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Information Needs ◽  
Vehicle Classification ◽  
The Internet ◽  
Parking Space ◽  
Automated Systems ◽  
The Internet Of Things

Edge data processing represents the new evolution of the Internet and Cloud computing. Its application to the Internet of Things (IoT) is a step towards faster processing of information from sensors for better performance. In automated systems, we have a large number of sensors, whose information needs to be processed in the shortest possible time and acted upon. The paper describes the possibility of applying Artificial Intelligence on Edge devices using the example of finding a parking space for a vehicle, and directing it based on the segment the vehicle belongs to. Algorithm of Machine Learning is used for vehicle classification, which is based on vehicle dimensions.

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