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

Abstract

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.

A Novel Multi-Qubit Quantum Key Distribution Ciphertext-Policy Attribute-Based Encryption Model to Improve Cloud Security for Consumers

“…Franson Interferometers were used to create a QKD standard in [24], but they lacked security. To secure cloud data, a dynamic, non-linear, and randomized quantum hash scheme was created [25]. A dynamic, non-linear, and randomized equation creates a chaotic key for encryption and decryption in this system.…”

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

“…The algorithm allows for the aring of secure keys while detecting any attempt of eavesdropping. [30][31][32][33][34][35][36] Across the globe, cloud providers facilitate the migration of cloud-based applications, software, and substantial data repositories into expansive data centers. However, a notable dilemma emerges as cloud users lack direct oversight over the information housed within these data centers.…”

An Efficient Hybrid QHCP-ABE Model to Improve Cloud Data Integrity and Confidentiality

“…This comprehensive method of key prior-dissemination techniques require stable computational and transmission costs. Developing the key policy-ABE process [35], Wang et al introduced a novel technique that stimulates portable node platform info security and consumer access annulment. The authors blended lethargic reencipherment and substitution-based re-encipherment concepts to attain consumer rights, privacy, consumer private key responsibility, and to decrease operating expenses.…”