scholarly journals Using Deep Reinforcement Learning to Improve Sensor Selection in the Internet of Things

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 95208-95222
Author(s):  
Hootan Rashtian ◽  
Sathish Gopalakrishnan
Author(s):  
Alex Mathew

There has been a rapid growth of the devices connected to the internet in the last decade for the various internet (IoT) of things applications. The increase of these smart devices has posed a great security concern in the internet of things ecosystem. The internet of things ecosystem must be protected from these threats. Reinforcement learning has been proposed by the cybersecurity professionals to provide the needed security tools for securing the IoT system since it is able to interact with the environment and learn how to detect the threats. This paper presents a comprehensive research on cybersecurity threats to the IoT system applications. The RL algorithms are also presented to understand the attacks on the IoT. Reinforcement learning is widely employed in cybersecurity because it can learn on its own experience by investigating and capitalizing on the unknown ecosystem, this enables it solve many complex problems. The RL capabilities on dealing with cybercrime challenges are also exploited in this paper.


2020 ◽  
pp. 1-12
Author(s):  
Zhang Caiqian ◽  
Zhang Xincheng

The existing stand-alone multimedia machines and online multimedia machines in the market have certain deficiencies, so they cannot meet the actual needs. Based on this, this research combines the actual needs to design and implement a multi-media system based on the Internet of Things and cloud service platform. Moreover, through in-depth research on the MQTT protocol, this study proposes a message encryption verification scheme for the MQTT protocol, which can solve the problem of low message security in the Internet of Things communication to a certain extent. In addition, through research on the fusion technology of the Internet of Things and artificial intelligence, this research designs scheme to provide a LightGBM intelligent prediction module interface, MQTT message middleware, device management system, intelligent prediction and push interface for the cloud platform. Finally, this research completes the design and implementation of the cloud platform and tests the function and performance of the built multimedia system database. The research results show that the multimedia database constructed in this paper has good performance.


2019 ◽  
pp. 4-44 ◽  
Author(s):  
Peter Thorns

This paper discusses the organisations involved in the development of application standards, European regulations and best practice guides, their scope of work and internal structures. It considers their respective visions for the requirements for future standardisation work and considers in more detail those areas where these overlap, namely human centric or integrative lighting, connectivity and the Internet of Things, inclusivity and sustainability.


2019 ◽  
Vol 14 (5) ◽  
pp. 375
Author(s):  
Vladimir P. Zhalnin ◽  
Anna S. Zakharova ◽  
Demid A. Uzenkov ◽  
Andrey I. Vlasov ◽  
Alexey I. Krivoshein ◽  
...  

2017 ◽  
Vol 10 ◽  
pp. 120-124
Author(s):  
R.S. Khisamov ◽  
◽  
R.A. Gabdrahmanov ◽  
A.P. Bespalov ◽  
V.V. Zubarev ◽  
...  

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