IBLIND Quantum Computing and HASBE for Secure Cloud Data Storage and Accessing

Singamaneni, Kranthi Kumar; Naidu, P. Sanyasi

doi:10.18280/ria.330106

Cited by 6 publications

(6 citation statements)

References 13 publications

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“…Likewise, many of the security measures currently utilized to protect that data cannot always do so adequately. Subsequently, the majority of third-party services currently offered still come with vulnerabilities that could leave users' sensitive private information open to theft and unauthorized access or exposure [37][38][39][40][41][42]. us, in order to directly enhance the approaches to security and privacy concerns regarding users' personal information, this work presents an approach in which such information is enciphered through a novel enhanced and dynamic nonpolynomial integrity centric quantum HCP-ABE prototype to store big cloud datasets prior to storage.…”

Section: Proposed Modelmentioning

confidence: 99%

An Enhanced Dynamic Nonlinear Polynomial Integrity-Based QHCP-ABE Framework for Big Data Privacy and Security

Singamaneni

Juneja²,

Abd‐Elnaby

et al. 2022

Security and Communication Networks

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Topics such as computational sources and cloud-based transmission and security of big data have turned out to be a major new domain of exploration due to the exponential evolution of cloud-based data and grid facilities. Various categories of cloud services have been utilized more and more widely across a variety of fields like military, army systems, medical databases, and more, in order to manage data storage and resource calculations. Attribute-based encipherment (ABE) is one of the more efficient algorithms that leads to better consignment and safety of information located within such cloud-based storage amenities. Many outmoded ABE practices are useful for smaller datasets to produce fixed-size cryptograms with restricted computational properties, in which their characteristics are measured as evidence and stagnant standards used to generate the key, encipherment, and decipherment means alike. To surmount the existing problems with such limited methods, in this work, a dynamic nonlinear poly randomized quantum hash system is applied to enhance the safety of cloud-based information. In the proposed work, users’ attributes are guaranteed with the help of a dynamic nonlinear poly randomized equation to initialize the chaotic key, encipherment, and decipherment. In this standard, structured and unstructured big data from clinical datasets are utilized as inputs. Real-time simulated outcomes demonstrate that the stated standard has superior exactness, achieving over 90% accuracy with respect to bit change and over 95% accuracy with respect to dynamic key generation, encipherment time, and decipherment time compared to existing models from the field and literature. Experimental results are demonstrated that the proposed cloud security standard has a good efficiency in terms of key generation, encoding, and decoding process than the conventional methods in a cloud computing environment.

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Section: Proposed Modelmentioning

confidence: 99%

An Enhanced Dynamic Nonlinear Polynomial Integrity-Based QHCP-ABE Framework for Big Data Privacy and Security

Singamaneni

Juneja²,

Abd‐Elnaby

et al. 2022

Security and Communication Networks

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“…encryption, and decryption time. [10] In this paper the authors explored a novel algorithm centered around blind quantum computing, aimed at fortifying the communication between a data owner and a cloud service provider (CSP). Additionally, we enhanced the hierarchical attribute-based encryption (ABE) algorithm by integrating BCQ (Blind Quantum Computing) key sharing.…”

Section: Related Workmentioning

confidence: 99%

Beyond Binary: The Capabilities of Classical and Quantum Computing for Securing Data Transmission

Prasad Paruchuri,

Veerapaneni,

Rames

et al. 2023

E3S Web Conf.

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In the present times, the demand for sophisticated encryption methods has escalated, especially for securing data transmission in vulnerable environments. These methods leverage diverse algorithms to fortify the integrity of communication channels. Quantum mechanics plays a pivotal role in two specific areas: quantum key distribution and property-based cryptography, both of which contribute to establishing secure communication protocols. This study focuses on conducting a comparative evaluation of classical and quantum cryptography, employing various cryptography algorithms. The objective is to ascertain the optimal algorithm within each realm classical and quantum cryptography for ensuring robust security.

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“…So, if all above mentioned constraints are satisfactory further the polynomial set of bi-linear curves can be valuated. This practice is efficiently combined with Bernoulli logistic map of family curves of the same type which provide more security in terms of chaotic randomization and enactment [17,23,24,49].…”

Section: Bi-linear Couplingmentioning

confidence: 99%

“…Block chain based QKD uses numerous internetwork communication links, which are a combination of secure quantum link and a general user info link [19,24,[36][37][38][39]. The source and destination together get a randomized pair of values on any place of G-bilinear cyclical group by adding cubits which are generated via different polarizers.…”

Section: Chaotic Key Making With Bqkdmentioning

confidence: 99%

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A Novel Blockchain and Bi-Linear Polynomial-Based QCP-ABE Framework for Privacy and Security over the Complex Cloud Data

Singamaneni

Ramana²,

Singh

et al. 2021

Sensors

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As a result of the limited resources available in IoT local devices, the large scale cloud consumer’s data that are produced by IoT related machines are contracted out to the cloud. Cloud computing is unreliable, using it can compromise user privacy, and data may be leaked. Because cloud-data and grid infrastructure are both growing exponentially, there is an urgent need to explore computational sources and cloud large-data protection. Numerous cloud service categories are assimilated into numerous fields, such as defense systems and pharmaceutical databases, to compute information space and allocation of resources. Attribute Based Encryption (ABE) is a sophisticated approach which can permit employees to specify a higher level of security for data stored in cloud storage facilities. Numerous obsolete ABE techniques are practical when applied to small data sets to generate cryptograms with restricted computational properties; their properties are used to generate the key, encrypt it, and decrypt it. To address the current concerns, a dynamic non-linear polynomial chaotic quantum hash technique on top of secure block chain model can be used for enhancing cloud data security while maintaining user privacy. In the proposed method, customer attributes are guaranteed by using a dynamic non- polynomial chaotic map function for the key initialization, encryption, and decryption. In the proposed model, both organized and unorganized massive clinical data are considered to be inputs for reliable corroboration and encoding. Compared to existing models, the real-time simulation results demonstrate that the stated standard is more precise than 90% in terms of bit change and more precise than 95% in terms of dynamic key generation, encipherment, and decipherment time.

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IBLIND Quantum Computing and HASBE for Secure Cloud Data Storage and Accessing

Cited by 6 publications

References 13 publications

An Enhanced Dynamic Nonlinear Polynomial Integrity-Based QHCP-ABE Framework for Big Data Privacy and Security

An Enhanced Dynamic Nonlinear Polynomial Integrity-Based QHCP-ABE Framework for Big Data Privacy and Security

Beyond Binary: The Capabilities of Classical and Quantum Computing for Securing Data Transmission

A Novel Blockchain and Bi-Linear Polynomial-Based QCP-ABE Framework for Privacy and Security over the Complex Cloud Data

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