A Review on Cloud Computing Security

Teo, Marry; Mahdin, Hairulnizam; Hwee, Lee Jia; Dicken, Haezel Ann; Hui, Tay Xin; Ling, Teng Mee; Azmi, Mohd Sanusi

doi:10.30630/joiv.2.4-2.171

Cited by 6 publications

(5 citation statements)

References 15 publications

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“…Check, ill-advised structure utilize, sneaking around, a web hack, giving up networks assults, and meeting seizure are the data-related threats to the cloud organization [27]. Even though Cloud computing could be seen as yet another peculiarity that could disrupt the Web's strategy, there are still a few things to be cautious about.…”

Section: Overviewmentioning

confidence: 99%

CNN Technique Security Inspection for Data Computing Networks

Ali¹

2023

wjps

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The hypothetical as well as system derivation have been shaped by data computing into the analysis of tomorrow. The global computing framework is rapidly influencing cloud development. The security aspects in a cloud-based computing environment remain at the middle of attention, despite the fact that it is important to take further period for could investigation by motivating it to separate fields. The development of cloud subordinate divisions and expert centers has resulted in the provision of optional mission design that is subject to cloud advancement. In order to guard against the potential consequences of being exposed to undesirable communal contests in cases such that, the cloud servers it is adjusted to store such data, weak info of various parameters is typically stored in servers using wireless locations with the presence of various cloud-based systems using geographically consumed info networks producers. The flexibility and benefits of cloud computing will be difficult to accept if the security is inadequate. This study examines cloud analyzing and cloud structure while also addressing security concerns and information computing standards. In addition, a new adversaries administration security strategy based on CNN will be proposed and compared to other readily available security regions. The obtained results for the CNN algorithm show a success rate of 100% with only 0.18 losses at batch number of 2*104. Also the confusion matrix show a very high classification measure for the trained samples among the target with resulting classes.

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Section: Overviewmentioning

confidence: 99%

CNN Technique Security Inspection for Data Computing Networks

Ali¹

2023

wjps

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“…In 2018, Marry Teo, et. al., [9] inspected the advancement of conveyed computing so much that to stay aware of the data in like manner application by using the central distant server with the web affiliation. By utilizing dispersed computing, the client can reduce their costs as they not a great explanation to purchase their own gear also programming.…”

Section: Literature Review and Related Workmentioning

confidence: 99%

Study of Information Computing Networks Security Investigation using CNN Technique

Ali¹

2022

IJASRE

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Information computing has molded the hypothetical as well as system derivation to tomorrow's analysis. Computing all over theplanet framework is quicklyacting into cloud development. Though it is significant for taking more time for could analyzing by moving it to separated areas, the security perspectives in a cloud-based computing environmental factors stay at the center of interest. Cloud subordinate divisions additionally expert centers have becoming progressed that have given elective mission design subject to cloud advancement. Against the introduction of different cloud-based networks with geographically dissipated information organization providers, fragile information of different components is normally saved in servers with remote situations against the possible results of becoming introduced to unwanted social events for situations where the cloud servers are settled to save such information. Atthe point when the security is not solid additionally fixed, the versatility, as well as advantages that cloud computing, offers that would be useful will have little acceptability. This study presents an investigation of theinformation computing standards similarly to security issues inherent inside the message concerning cloud analyzing with cloud structure. Additionally, an upgraded security strategy utilizing CNN will be proposed for enemies of assaults administration that will be contrasted and otheraccessible security geographies

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“…Because of the distributed nature of CC networks, it is easier for attackers to find weaknesses in the system and exploit them to obtain information [15], [16]. When a CC network operates using wireless communications, it becomes more vulnerable to a MiTM attacks.…”

Section: B Related Workmentioning

confidence: 99%

Convolutional Neural Network Framework for Encrypted Image Classification in Cloud-Based ITS

Lidkea

Mureşan

Al-Dweik

2020

IEEE Open J. Intell. Transp. Syst.

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Internet of Things (IoT) and Cloud Computing (CC) technologies are becoming critical requirements to the advancement of intelligent transportation systems (ITSs). ITSs generally rely on captured images to evaluate the status of traffic and perform vehicle statistics. However, such images may contain confidential information, and thus, securing such images is paramount. Therefore, we propose in this paper an efficient framework for improving the security of CC-IoT based ITSs. The proposed framework allows extracting particular vehicle information without revealing any sensitive information. Towards this goal, a convolutional neural network is used to classify encrypted images, based on the vehicle type in real-time, obtained by cameras integrated into road-side units that are part of an ITS leaving sensitive information in all images hidden. Within the proposed framework, we develop a new image classification architecture that never fully decrypts the captured images, thus protecting drivers' personal information, such as location, license plate, and vehicle contents. In addition, the system does not require a fully decrypted image, which increases the system computational efficiency as compared to conventional systems. The obtained results show that the proposed partial decryption classification technique presents up to 18% reduction in average computational complexity when compared with a fully decrypted system.

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A Review on Cloud Computing Security

Cited by 6 publications

References 15 publications

CNN Technique Security Inspection for Data Computing Networks

CNN Technique Security Inspection for Data Computing Networks

Study of Information Computing Networks Security Investigation using CNN Technique

Convolutional Neural Network Framework for Encrypted Image Classification in Cloud-Based ITS

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