An approach for big data security based on Hadoop distributed file system

Mahmoud, Hadeer; Hegazy, Abdelfatah; Khafagy, Mohamed Helmy

doi:10.1109/itce.2018.8316608

Cited by 36 publications

(11 citation statements)

References 4 publications

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“…Hence, to adress these concerns, the researchers of this study have propositioned a new encryption-decryption algorithm, i.e., the ABHE. As per the simulation results, this technique has shown marked improvements over encryption-decryption time in comparison with the already available algorithms including the Advanced Encryption Standard (AES) and AES with OTP (Mahmoud, Hegazy & Khafagy, 2018).…”

Section: Introductionmentioning

confidence: 60%

“…Data encryption based on AES and OTP. This research paper (Mahmoud, Hegazy & Khafagy, 2018) has highlighted a method to improve the upload and download time with reduction of encrypted file size by AES and OTP algorithms in HDFS. The authors performed encryption and decryption by two different ways which are based on AES and AES-OTP algorithms.…”

Section: Secure Multi Sharing In Big Data Storagementioning

confidence: 99%

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Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective

Kapil

Agrawal

Attaallah

et al. 2020

PeerJ Computer Science

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Hadoop has become a promising platform to reliably process and store big data. It provides flexible and low cost services to huge data through Hadoop Distributed File System (HDFS) storage. Unfortunately, absence of any inherent security mechanism in Hadoop increases the possibility of malicious attacks on the data processed or stored through Hadoop. In this scenario, securing the data stored in HDFS becomes a challenging task. Hence, researchers and practitioners have intensified their efforts in working on mechanisms that would protect user’s information collated in HDFS. This has led to the development of numerous encryption-decryption algorithms but their performance decreases as the file size increases. In the present study, the authors have enlisted a methodology to solve the issue of data security in Hadoop storage. The authors have integrated Attribute Based Encryption with the honey encryption on Hadoop, i.e., Attribute Based Honey Encryption (ABHE). This approach works on files that are encoded inside the HDFS and decoded inside the Mapper. In addition, the authors have evaluated the proposed ABHE algorithm by performing encryption-decryption on different sizes of files and have compared the same with existing ones including AES and AES with OTP algorithms. The ABHE algorithm shows considerable improvement in performance during the encryption-decryption of files.

show abstract

Section: Introductionmentioning

confidence: 60%

Section: Secure Multi Sharing In Big Data Storagementioning

confidence: 99%

Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective

Kapil

Agrawal

Attaallah

et al. 2020

PeerJ Computer Science

View full text Add to dashboard Cite

show abstract

“…Hence, to adress these concerns, the researchers of this study have propositioned a new encryption-decryption algorithm, i.e., the ABHE. As per the simulation results, this technique has shown marked improvements over encryptiondecryption time in comparison with the already available algorithms including the Advanced Encryption Standard (AES) and AES with OTP [27]. The main contributions of paper are :…”

Section: Introductionmentioning

confidence: 84%

“…This research paper [27] has highlighted a method to improve the upload and download time with reduction of encrypted file size by AES and OTP algorithms in HDFS. The authors performed encryption and decryption by two different ways which are based on AES and AES-OTP algorithms.…”

Section: Data Encryption Based On Aes and Otpmentioning

confidence: 99%

Peer Review #2 of "Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective (v0.1)"

2020

View full text Add to dashboard Cite

Hadoop has become a promising platform to reliably process and store big data. It provides flexible and low cost services to huge data through Hadoop Distributed File System (HDFS) storage. Unfortunately, absence of any inherent security mechanism in Hadoop increases the possibility of malicious attacks on the data processed or stored through Hadoop. In this scenario, securing the data stored in HDFS becomes a challenging task. Hence, researchers and practitioners have intensified their efforts in working on mechanisms that would protect user's information collated in HDFS. This has led to the development of numerous encryption-decryption algorithms but their performance decreases as the file size increases. In the present study, the authors have enlisted a methodology to solve the issue of data security in Hadoop storage. The authors have integrated Attribute Based Encryption with the honey encryption on Hadoop, i.e., Attribute Based Honey Encryption (ABHE). This approach works on files that are encoded inside the HDFS and decoded inside the Mapper. In addition, the authors have evaluated the proposed ABHE algorithm by performing encryption-decryption on different sizes of files and have compared the same with existing ones including AES and AES with OTP algorithms. The ABHE algorithm shows considerable improvement in performance during the encryption-decryption of files.

show abstract

“…Different ciphered schemes were developed and employed for the sake of information security. Hence the two main categories are: (i) Symmetric-key (secret key) cryptosystems [14] like advanced encryption standard (AES), data encryption standard (DES), and triple DES (ii) asymmetric-key ( public key) algorithms [15] like elliptic curve diffie-hellman (ECDH) and RSA. The proposed approach is considered as an attempt to improve what was presented by the paper [13] at both of encipherment/decipherment procedures for securing files of big data-based hadoop-integrated AES and OTP algorithms [16].…”

mentioning

confidence: 99%

An approach for enhancing data confidentiality in Hadoop

Kareem

Yousif²,

Abdalwahid

2020

IJEECS

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<p class="Abstract">The amount of data processed and stored in the cloud is growing dramatically. The traditional storage devices at both hardware and software levels cannot meet the requirement of the cloud. This fact motivates the need for a platform which can handle this problem. Hadoop is a deployed platform proposed to overcome this big data problem which often uses MapReduce architecture to process vast amounts of data of the cloud system. Hadoop has no strategy to assure the safety and confidentiality of the files saved inside the Hadoop distributed File system(HDFS). In the cloud, the protection of sensitive data is a critical issue in which data encryption schemes plays avital rule. This research proposes a hybrid system between two well-known asymmetric key cryptosystems (RSA, and Paillier) to encrypt the files stored in HDFS. Thus before saving data in HDFS, the proposed cryptosystem is utilized for encrypting the data. Each user of the cloud might upload files in two ways, non-safe or secure. The hybrid system shows higher computational complexity and less latency in comparison to the RSA cryptosystem alone.</p>

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An approach for big data security based on Hadoop distributed file system

Cited by 36 publications

References 4 publications

Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective

Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective

Peer Review #2 of "Attribute based honey encryption algorithm for securing big data: Hadoop distributed file system perspective (v0.1)"

An approach for enhancing data confidentiality in Hadoop

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