A Hierarchic Secure Cloud Storage Scheme Based on Fog Computing

Zhou, Jiyuan; Bhuiyan, Zakirul Alam; Liu, Anfeng

doi:10.1109/dasc-picom-datacom-cyberscitec.2017.90

Cited by 9 publications

(3 citation statements)

References 17 publications

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“…In the medical imaging system, accessing time is reduced by using cloud nearer edge system [26]. The system design allows the user to access the medical images within their scope.…”

Section: Wearable Healthcare Devicesmentioning

confidence: 99%

A Four-Layer Robust Storage in Cloud using Privacy Preserving Technique with Reliable Computational Intelligence in Fog-Edge

2020

KSII TIIS

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The proposed framework of Four Layer Robust Storage in Cloud (FLRSC) architecture involves host server, local host and edge devices in addition to Virtual Machine Monitoring (VMM). The goal is to protect the privacy of stored data at edge devices. The computational intelligence (CI) part of our algorithm distributes blocks of data to three different layers by partially encoded and forwarded for decoding to the next layer using hash and greed Solomon algorithms. VMM monitoring uses snapshot algorithm to detect intrusion. The proposed system is compared with Tiang Wang method to validate efficiency of data transfer with security. Hence, security is proven against the indexed efficiency. It is an important study to integrate communication between local host software and nearer edge devices through different channels by verifying snapshot using lamport mechanism to ensure integrity and security at software level thereby reducing the latency. It also provides thorough knowledge and understanding about data communication at software level with VMM. The performance evaluation and feasibility study of security in FLRSC against three-layered approach is proven over 2 32 blocks of data with 98% accuracy. Practical implications and contributions to the growing knowledge base are highlighted along with directions for further research.

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“…In the medical imaging system, accessing time is reduced by using cloud nearer edge system [26]. The system design allows the user to access the medical images within their scope.…”

Section: Wearable Healthcare Devicesmentioning

confidence: 99%

A Four-Layer Robust Storage in Cloud using Privacy Preserving Technique with Reliable Computational Intelligence in Fog-Edge

2020

KSII TIIS

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“…Compared with cloud computing, it is closer to the data owner. In data transmission, the fog node layer is added to reduce the delay and bandwidth [11], [12]. Hu et al [13] proposed a security and privacy protection scheme based on the fog computing framework, which did not consider the data transmission model in the fog computing framework.…”

Section: Introductionmentioning

confidence: 99%

Data Integrity Audit Based on Data Blinding for Cloud and Fog Environment

Bian

Shao

et al. 2022

IEEE Access

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Cloud-fog computing is a novel computing model that expands the functionality of cloud computing, which provides various services through fog nodes. The issue of traditional data integrity auditing are low data security, slow data processing speed and low communication efficiency. To solve these problems, this paper proposes a data integrity audit scheme based on data blinding. This scheme uses the edge devices in the transmission node to establish a fog computing layer between the cloud service provider and the data owner to reduce transmission delay. The subordinate distribution relationship and weight between fog nodes dynamically allocate the optimal path and transmit the data to reduce transmission delay. At the same time, a blind factor is added to the integrity audit in the evidence generation process to avoid data leakage. This paper gives a security model and security proof based on computational Diffie-Hellman (CDH) assumptions. The experimental results show that the fog computing layer and blind factor are introduced into the data integrity audit process, which can reduce the data communication delay effectively and improve the security of data audit.INDEX TERMS Cloud and fog computing, data blinding, integrity audit, cloud storage.

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“…Fog computing, also known as edge computing, is a growing trend in the computing domain as cloud computing has issues with security, latency, and high running costs. Adding an extra layer of computing offers better localization of data and better security [4], [5]. As the middle layer computes data from fewer number of nodes with less data, the computing time and power consumption also reduces.…”

Section: Introductionmentioning

confidence: 99%

LoRa based Architecture for Fault Localization in Transmission Lines

Gohil¹,

Parmar²

2020

IJCA

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In a cloud computing based sensor network, nodes transmit data to the cloud and then data is processed on the cloud. The central processing performed on the cloud consumes precious computing time due to vast amounts of data. In some scenarios, processing can have time constraints. If the data processing can be done using simple algorithms, edge nodes of the sensor network can be used to save transmission and computing time. A concept of fog computing has been introduced here that includes a layer of hierarchy in cloud computing architecture that processes the initial data and quickens the decision-making process. In this research, a fog computing concept is explored for fault localization in transmission lines and distribution networks. In transmission lines and overhead distribution network, the fault detection is very crucial and should take minimum time. When a longrange (LoRa) transceiver based fault indicator is realized for increased range, it presents various challenges to the existing architecture. As the number of data concentrator nodes reduce due to higher range of LoRa, the fault localization complexity increases. In this research, fault indicators are installed with GPS coordinates to reduce complexity for fault localization. Two fault indicators are paired to localize the fault in the transmission lines. To find the location of the fault faster than the time-consuming process of the cloud computing, a new hierarchical layer of fog node is introduced in the system. This new architecture is compared with the earlier system, and the pros and cons are discussed in this research.

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A Hierarchic Secure Cloud Storage Scheme Based on Fog Computing

Cited by 9 publications

References 17 publications

A Four-Layer Robust Storage in Cloud using Privacy Preserving Technique with Reliable Computational Intelligence in Fog-Edge

A Four-Layer Robust Storage in Cloud using Privacy Preserving Technique with Reliable Computational Intelligence in Fog-Edge

Data Integrity Audit Based on Data Blinding for Cloud and Fog Environment

LoRa based Architecture for Fault Localization in Transmission Lines

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