Mobile Multi-agent Systems for the Internet-of-Things and Clouds Using the JavaScript Agent Machine Platform and Machine Learning as a Service

Author(s):  
Stefan Bosse
2020 ◽  
pp. 23-31
Author(s):  
Andrey Stepenkin ◽  

The capabilities of robotic systems are growing rapidly. The ways of operating such systems are increasing every day. Sensor networks, the Internet of Things, cyber-physical systems have similar properties as multi-agent robotic systems, which allows us to consider the approaches and methods of ensuring security used in them. Purpose of the article: improving the security of multi-agent systems in an uncontrolled environment, developing methods for assessing trust of the environment. Research methods: analysis of existing threat models for multi-agent robotic systems, as well as systems with similar properties: cyber-physical systems and the Internet of things. Analysis of the research results of existing approaches to ensuring the security of multi-agent systems. The results: an analysis of security threats and existing methods of ensuring security for robotic multi-agent systems, as well as systems with similar properties, was carried out. An extension for security methods based on trust and reputation has been developed, taking into account the operating environment of the system as part of information interaction. A method for localizing the subject of an external intruder in the environment is proposed.


2020 ◽  
Vol 34 (05) ◽  
pp. 7317-7324
Author(s):  
Leonit Zeynalvand ◽  
Tie Luo ◽  
Jie Zhang

Trust and reputation management (TRM) plays an increasingly important role in large-scale online environments such as multi-agent systems (MAS) and the Internet of Things (IoT). One main objective of TRM is to achieve accurate trust assessment of entities such as agents or IoT service providers. However, this encounters an accuracy-privacy dilemma as we identify in this paper, and we propose a framework called Context-aware Bernoulli Neural Network based


Telecom IT ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 50-55
Author(s):  
D. Saharov ◽  
D. Kozlov

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.


2021 ◽  
Vol 19 (3) ◽  
pp. 163
Author(s):  
Dušan Bogićević

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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