Secure Cloud Storage Service Using Bloom Filters for the Internet of Things

Jeong, Junho; Joo, Jong Wha J.; Lee, Yang Sun; Son, Yunsik

doi:10.1109/access.2019.2915576

Cited by 17 publications

(8 citation statements)

References 27 publications

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“…Using a BF, the authors (Jeong et al, 2019) proposed a secure storage service for IoT environments based on a provable data possession model. Their proposed scheme is not based on a public key, such as Rivest-Shamir-Adleman (RSA), bilinear mapping, and homomorphism.…”

Section: Using Filters In Iot Applicationsmentioning

confidence: 99%

An efficient filter with low memory usage for multimedia data of industrial Internet of Things

Goudarzi

Rahmani

2021

PeerJ Computer Science

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One of the essential concerns of Internet of Things (IoT) is in industrial systems or data architecture to support the evolutions in transportation and logistics. Considering the Industrial IoT (IIoT) openness, the need for accessibility, availability, and searching of data has rapidly increased. The primary purpose of this research is to propose an Efficient Two-Dimensional Filter (ETDF) to store multimedia data of IIoT applications in a specific format to achieve faster response and dynamic updating. This filter consists of a two-dimensional array and a hash function integrated into a cuckoo filter for efficient use of memory. This study evaluates the scalability of the filter by increasing the number of requests from 10,000 to 100,000. To assess the performance of the proposed filter, we measure the parameters of access time and lookup message latency. The results show that the proposed filter improves the access time by 12%, compared to a Fast Two-Dimensional Filter (FTDF). Moreover, it improves memory usage by 20% compared to FTDF. Experiments indicate a better access time of the proposed filter compared to other filters (i.e., Bloom, quotient, cuckoo, and FTD filters). Insertion and deletion times are essential parameters in comparing filters, so they are also analyzed.

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Section: Using Filters In Iot Applicationsmentioning

confidence: 99%

An efficient filter with low memory usage for multimedia data of industrial Internet of Things

Goudarzi

Rahmani

2021

PeerJ Computer Science

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“…J. Jeong, J. W. J. Joo, Y. Lee and Y. Son, [14] "Secure Cloud Storage Service Using Bloom Filters for the Internet of Things," in the article identify the need for data integrity verification which is usually done by third party. The authors proposed a provable data possession model using Bloom Filter.…”

Section: Literature Surveymentioning

confidence: 99%

Data Membership Identification using Bloom Filter in Cloud Storage for Effective Resource Allocation

Jain¹

2021

ITII

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Cloud computing has recently been the buzz word that had changed the entire software industry with its PaaS, IaaS and SaaS architecture model. The legacy systems operational in the organizations across different industries have been using the database that had an overhead in terms of cost of data storage, runtime operation and frequent data maintenance. Cloud database concept had challenged the existing storage and operational norms of data. In the distributed environment, resources used in the cloud databases need to identify whether the requested data belongs to the data nodes of a cluster. With databases began to be ubiquitous, the data storage needed to satisfy heterogeneous data structures rather the unstructured data storage support is looked for. The Use of Bloom's filter for data membership identification is the novel approach and can effectively improve the resource organization strategy on cloud. Dynamic resource organization can further improve the query efficiency as well. The concern raised during this is the data privacy which can also be ascertain by maintaining the data access authority levels. Bloom filter uses less memory space against the large dataset to store it's information. A Bloom filter is proposed to be used to determine whether an element is part of a reference set. It is a very compact hash-based data structure with efficient look-up times and a manageable risk of giving false positives.

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“…Jeong et al [ 9 ] presented an effective data possession verification scheme based on the use of the Bloom Filter (BF) [ 57 ]. The developed schema imposes a consistency guarantee on large volumes of data generated by low computational devices (Internet of Things) and stored in cloud services.…”

Section: Related Workmentioning

confidence: 99%

“…The monitoring of the integrity of files stored in the cloud has been the subject of several studies [ 5 , 6 , 7 , 8 , 9 ], which adopted different mechanisms and technologies. Pinheiro et al [ 10 ] presented a protocol designed for the periodic monitoring of the integrity of large stored files based on computational trust and symmetric cryptography.…”

Section: Introductionmentioning

confidence: 99%

Validation of Architecture Effectiveness for the Continuous Monitoring of File Integrity Stored in the Cloud Using Blockchain and Smart Contracts

Pinheiro

Canedo

Albuquerque

et al. 2021

Sensors

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The management practicality and economy offered by the various technological solutions based on cloud computing have attracted many organizations, which have chosen to migrate services to the cloud, despite the numerous challenges arising from this migration. Cloud storage services are emerging as a relevant solution to meet the legal requirements of maintaining custody of electronic documents for long periods. However, the possibility of losses and the consequent financial damage require the permanent monitoring of this information. In a previous work named “Monitoring File Integrity Using Blockchain and Smart Contracts”, the authors proposed an architecture based on blockchain, smart contract, and computational trust technologies that allows the periodic monitoring of the integrity of files stored in the cloud. However, the experiments carried out in the initial studies that validated the architecture included only small- and medium-sized files. As such, this paper presents a validation of the architecture to determine its effectiveness and efficiency when storing large files for long periods. The article provides an improved and detailed description of the proposed processes, followed by a security analysis of the architecture. The results of both the validation experiments and the implemented defense mechanism analysis confirm the security and the efficiency of the architecture in identifying corrupted files, regardless of file size and storage time.

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Secure Cloud Storage Service Using Bloom Filters for the Internet of Things

Cited by 17 publications

References 27 publications

An efficient filter with low memory usage for multimedia data of industrial Internet of Things

An efficient filter with low memory usage for multimedia data of industrial Internet of Things

Data Membership Identification using Bloom Filter in Cloud Storage for Effective Resource Allocation

Validation of Architecture Effectiveness for the Continuous Monitoring of File Integrity Stored in the Cloud Using Blockchain and Smart Contracts

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