Block Level Data-Deduplication and Security Using Convergent Encryption to Offer Proof of Verification

Reddy, B. Tirapathi; Kiran, P. Sai; Priyanandan, T.; Ch, Smitha Chowdary; Aditya, B. Jaya

doi:10.1109/icoei48184.2020.9143055

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…We can ensure the confidentiality of data in the cloud by traditional encryption, but it is incompatible with the de-duplication of data. On the other hand, different cipher texts would duplicate data copies to different users, making de-duplication difficult [13] [14].To maintain security, data owners encrypt their data before transferring this data to the cloud [15]. But how does a cloud service decide if the same text is the product of multiple encrypted texts [16].…”

Section: Introductionmentioning

confidence: 99%

‏An Enhanced Approach to Improve the Security and Performance for Deduplication

Almrezeq¹

2021

TURCOMAT

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Cloud service providers providing users with efficient and effective storage and transmission of data. To reduce storage costs and save bandwidth, cloud service providers are attracted to use data de-duplication feature. Cloud users are interested in using the cloud safely and privately to protect the data they share on the cloud. Therefore, they encrypt the data before uploading it to the cloud. Since the intent of encryption conflicts with the de-duplication function, the data de-duplication feature becomes a hard problem. Existing de-duplication methods are ineffective in terms of both security and efficiency. They are either vulnerable to brute force attacks that enable the attacker to retrieve files, or they are computationally expensive. That is what drives us to suggest a method for removing duplicate data that is both performance and security effective. We'll start with a description of the implementations and functionality of de-duplication strategies, then move on to the literature that proposes various approaches to de-duplication and the security and efficiency problems that existing approaches face. Via the use of the AES-CBC algorithm and hashing functions, we have proposed an enhancement to improves the performance and protection of data de-duplication for users. Without the involvement of a third party, users' keys are created in a consistent and safe manner. We prove the efficacy of the recommended solution by putting it into practice and comparison with the existing techniques.

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Section: Introductionmentioning

confidence: 99%

‏An Enhanced Approach to Improve the Security and Performance for Deduplication

Almrezeq¹

2021

TURCOMAT

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Privacy Preserving Data Deduplication in cloud using Advanced Encryption Standard

Reddy

Vaishnavi

Lalitha

et al. 2021

2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS)

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Fingerprint-Based Data Deduplication Using a Mathematical Bounded Linear Hash Function

Saeed

George

2021

Symmetry

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Due to the quick increase in digital data, especially in mobile usage and social media, data deduplication has become a vital and cost-effective approach for removing redundant data segments, reducing the pressure imposed by enormous volumes of data that must be kept. As part of the data deduplication process, fingerprints are employed to represent and identify identical data blocks. However, when the amount of data increases, the number of fingerprints grows as well, and due to the restricted memory size, the speed of data deduplication suffers dramatically. Various deduplication solutions show a bottleneck in the form of matching lookups and chunk fingerprint calculations, for which we pay in the form of storage and processors needed for storing hashes. Utilizing a fast hash algorithm to improve the fingerprint lookup performance is an appealing challenge. Thus, this study is focused on enhancing the deduplication system by suggesting a novel and effective mathematical bounded linear hashing algorithm that decreases the hashing time by more than two times compared to MD5 and SHA-1 and reduces the size of the hash index table by 50%. Due to the enormous number of chunk hash values, looking up and comparing hash values takes longer for large datasets; this work offers a hierarchal fingerprint lookup strategy to minimize the hash judgement comparison time by up to 78%. Our suggested system reduces the high latency imposed by deduplication procedures, primarily the hashing and matching phases. The symmetry of our work is based on the balance between the proposed hashing algorithm performance and its reflection on the system efficiency, as well as evaluating the approximate symmetries of the hashing and lookup phases compared to the other deduplication systems.

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Block Level Data-Deduplication and Security Using Convergent Encryption to Offer Proof of Verification

Cited by 3 publications

References 14 publications

‏An Enhanced Approach to Improve the Security and Performance for Deduplication

‏An Enhanced Approach to Improve the Security and Performance for Deduplication

Privacy Preserving Data Deduplication in cloud using Advanced Encryption Standard

Fingerprint-Based Data Deduplication Using a Mathematical Bounded Linear Hash Function

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