Security Threats of Cloud Computing

Aawadallah, Nancy

doi:10.17762/ijritcc2321-8169.1504133

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…This is complicated issue inside the cloud, which offers assets connecting the clients; if assets change, that could affect information trustworthiness [41,42]. Next is poor client access control, which because of inefficient access and character control has various issues and threats that enable assailants harm information assets [43,44]. 3.…”

Section: Cloud Security Threatsmentioning

confidence: 99%

A Review of Machine Learning Algorithms for Cloud Computing Security

et al. 2020

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Cloud computing (CC) is on-demand accessibility of network resources, especially datastorage and processing power, without special and direct management by the users. CC recentlyhas emerged as a set of public and private datacenters that offers the client a single platform acrossthe Internet. Edge computing is an evolving computing paradigm that brings computation andinformation storage nearer to the end-users to improve response times and spare transmissioncapacity. Mobile CC (MCC) uses distributed computing to convey applications to cell phones.However, CC and edge computing have security challenges, including vulnerability for clients andassociation acknowledgment, that delay the rapid adoption of computing models. Machine learning(ML) is the investigation of computer algorithms that improve naturally through experience. In thisreview paper, we present an analysis of CC security threats, issues, and solutions that utilizedone or several ML algorithms. We review different ML algorithms that are used to overcomethe cloud security issues including supervised, unsupervised, semi-supervised, and reinforcementlearning. Then, we compare the performance of each technique based on their features, advantages,and disadvantages. Moreover, we enlist future research directions to secure CC models.

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Section: Cloud Security Threatsmentioning

confidence: 99%

A Review of Machine Learning Algorithms for Cloud Computing Security

et al. 2020

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“…To reduce the duration of construction, reduce the risk of injury to workers and perform construction work in extremely harsh conditions, many researchers are considering the idea of introducing autonomous robots for construction work [1,2]. The use of robots in construction will reduce the number of time-consuming operations and construction time; will provide the opportunity to obtain complex geometric shapes that require significant labor and time costs [3]. Construction companies introducing robots into the technological process will be able to get a great advantage over competitors, increasing their efficiency using all kinds of specialized robots, robotic manipulators and drones.…”

Section: Introduction Plastering Workmentioning

confidence: 99%

Automation of the process of applying plaster on the walls of agricultural premises

2020

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Plastering works are distinguished by complex technology and the use of a large number of manual working methods. Eliminate manual labor, significantly increase productivity and improve the quality of the plastering is possible based on the automation of applying plaster. The article discusses two ways to control the amount of plaster mixture: direct regulation of the amount of plaster mixture by changing the performance of the nozzle and regulation of the amount of plaster mixture by optimizing the speed of the nozzle. The disadvantage of the first method is the need for preliminary calculation of the time instant of the nozzle productivity change. The difficulty in solving this problem is due to the inertia of the device. In connection with these difficulties, it is proposed to use the second method of adjusting the amount of plaster mixture by optimizing the speed of the nozzle. The simulation of the proposed control system was carried out in the Matlab Simulink. The developed technique for applying plaster during automatic adjustment of the nozzle speed provides the necessary speed of the working tool depending on the surface irregularities.

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