A Comparison of Data Fragmentation Techniques in Cloud Servers

Lentini, Salvatore; Grosso, Enrico; Masala, Giovanni Luca

doi:10.1007/978-3-319-75928-9_50

Cited by 4 publications

(5 citation statements)

References 8 publications

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“…In the first part of this paper we are aiming to analyze the performance of using data fragmentation on different cloud providers, as well as the performance of the connection type. This work investigates the performance of the most promising pattern fragmentation technique [12] in a virtual machine hosted by Amazon Web Services (AWS) [17], in comparison with the cloud offered by Microsoft Azure [18]. During the investigation, we always consider sending the files to a single provider via a secure connection.…”

Section: Resultsmentioning

confidence: 99%

“…Bahramim et al [10] investigates the use of databases to store and manage chunks created with the same method and adding a layer of encryption to the database. Lentini et al [12] measured the performance of different fragmentation techniques on Amazon Web Services and compared them with the AES cryptography.…”

Section: State Of the Artmentioning

confidence: 99%

“…In the random pattern fragmentation (RPF), originally proposed by [9][10], but referencing the version implemented in [12], the original file is divided into N chunks and the pattern indexes are created with a random function, in other words, a random permutation of N elements before being stored in split files. The split files, are then saved on a cloud instance.…”

Section: Random Pattern Fragmentationmentioning

confidence: 99%

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Big Data Security on Cloud Servers Using Data Fragmentation Technique and NoSQL Database

Santos

Masala

2018

Intelligent Interactive Multimedia Systems and Services

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Cloud computing has become so popular that most sensitive data are hosted on the cloud. This fast-growing paradigm has brought along many problems, including the security and integrity of the data, where users rely entirely on the providers to secure their data. This paper investigates the use of the pattern fragmentation to split data into chunks before storing it in the cloud, by comparing the performance on two different cloud providers. In addition, it proposes a novel approach combining a pattern fragmentation technique with a NoSQL database, to organize and manage the chunks. Our research has indicated that there is a trade-off on the performance when using a database. Any slight difference on a big data environment is always important, however, this cost is compensated by having the data organized and managed. The use of random pattern fragmentation has great potential, as it adds a layer of protection on the data without using as much resources, contrary to using encryption.

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Section: Resultsmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Section: Random Pattern Fragmentationmentioning

confidence: 99%

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Big Data Security on Cloud Servers Using Data Fragmentation Technique and NoSQL Database

Santos

Masala

2018

Intelligent Interactive Multimedia Systems and Services

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“…The year 2018 focuses on data fragmentation strategies and how they can impact the overall performance of a cloud service [7]. Using Amazon Web Services, an analysis of the time taken to execute each algorithm based on pattern fragmentation, cipher, or both.…”

Section: -A Comparison Of Data Fragmentation Techniques In Cloud Serversmentioning

confidence: 99%

A Review for Data Fragmentation in Cloud Computing

Abed¹,

Tawil²

2022

IJRST

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The importance of network security is demonstrated by preserving data from being stolen or tampered with by attackers. The computerized cloud supports the protection of both large and small data as well as authorized remote access. Although its protection is secured in the cloud, it needs to use additional methods to enhance data protection from attackers. In this paper, we present the various methods that researchers used to protect data through the computerized cloud, as the diversity in the use of methods led to obtaining good results, albeit to varying degrees. This relieved data fragmentation using multiple technologies and storing it in the cloud, and some used data encryption methods. The aim of this research is to present different types of methods used in the field of data protection across the network via the cloud, which provides an opportunity for researchers to present research that addresses the gaps in order to obtain better results

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“…Finally, the split files are then sent to the database, where each split file is saved as a row in the table. Unlike other related approaches, such as [32] and [36], the proposed method does not track the header and footer of the file, nor it adds padding to chunks to ensure they are all the same size. This is due to the unwanted performance overhead that both practices introduce.…”

Section: A Random Pattern Fragmentation (Rpf)mentioning

confidence: 99%

Enhancing Data Security in Cloud using Random Pattern Fragmentation and a Distributed NoSQL Database

Santos

Ghita

Masala

2019

2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)

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The cloud computing model has become very popular among users, as it has proven to be a cost-effective solution to store and process data, thanks to recent advancements in virtualization and distributed computing. Nevertheless, in the cloud environment, the user entrusts the safekeeping of its data entirely to the provider, which introduces the problem of how secure such data is and whether its integrity has been maintained. This paper proposes an approach to the data security in cloud by utilizing a random pattern fragmentation algorithm and combine it with a distributed NoSQL database. This not only increases the security of the data by storing it in different nodes and scramble all the bytes, but also allows the user to implement an alternative method of securing data. The performance of the approach is compared to other approaches, along with AES 256 encryption. Results indicate a significant performance improvement over encryption, highlighting the capabilities of this method in cloud, as it creates a layer of protection without additional overhead.

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A Comparison of Data Fragmentation Techniques in Cloud Servers

Cited by 4 publications

References 8 publications

Big Data Security on Cloud Servers Using Data Fragmentation Technique and NoSQL Database

Big Data Security on Cloud Servers Using Data Fragmentation Technique and NoSQL Database

A Review for Data Fragmentation in Cloud Computing

Enhancing Data Security in Cloud using Random Pattern Fragmentation and a Distributed NoSQL Database

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