Cloud data protection using weibull distributed recurrent neural ergodic signcryption (Record no. 22711)
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| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250424142119.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250424b xxu||||| |||| 00| 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | AIKTC-KRRC |
| Transcribing agency | AIKTC-KRRC |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| 9 (RLIN) | 25980 |
| Author | Mala, J. |
| 245 ## - TITLE STATEMENT | |
| Title | Cloud data protection using weibull distributed recurrent neural ergodic signcryption |
| 250 ## - EDITION STATEMENT | |
| Volume, Issue number | Vol.15(2), Oct |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Chennai |
| Name of publisher, distributor, etc. | ICT Academy |
| Year | 2024 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Pagination | 3497-3504p. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Cloud computing has become an integral part of modern computing,<br/>offering scalable storage and processing resources. However, the<br/>security of data stored in the cloud remains a major concern, especially<br/>when dealing with sensitive information. Traditional encryption<br/>schemes, while effective, often face limitations in terms of<br/>computational overhead and vulnerability to advanced attacks. To<br/>address these challenges, we propose a novel Weibull Distributed<br/>Recurrent Neural Ergodic Skewed Certificateless Signcryption scheme<br/>aimed at enhancing data protection in cloud environments. The key<br/>problem addressed by this work is the inherent inefficiency of existing<br/>cryptographic solutions that either rely on certificate-based systems or<br/>suffer from high computational and communication costs. This is<br/>especially crucial in cloud systems where real-time data processing is<br/>essential. Our approach integrates Weibull distribution for key<br/>management and optimization, recurrent neural networks (RNNs) for<br/>secure data transmission prediction, and ergodic skewed signcryption<br/>to eliminate the need for certificate authorities. This results in improved<br/>security, reduced computational overhead, and efficient<br/>communication, ensuring that the data remains secure even in dynamic<br/>cloud environments. The proposed scheme was tested using various<br/>metrics, including encryption/decryption time, data throughput, and<br/>attack resistance. Results demonstrate a significant reduction in<br/>computational cost by approximately 28% compared to traditional<br/>certificateless encryption. Furthermore, encryption times decreased<br/>from an average of 1.8 ms to 1.2 ms, and the scheme showed robustness<br/>against man-in-the-middle and chosen-ciphertext attacks with a<br/>detection accuracy of 98.6%. These results confirm the efficacy of the<br/>proposed system for enhancing security in cloud computing<br/>environments while maintaining high performance. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| 9 (RLIN) | 4622 |
| Topical term or geographic name entry element | Computer Engineering |
| 773 0# - HOST ITEM ENTRY | |
| Place, publisher, and date of publication | Chennai ICT Academy |
| Title | ICTACT Journal on Soft Computing (IJSC) |
| 856 ## - ELECTRONIC LOCATION AND ACCESS | |
| URL | https://ictactjournals.in/paper/IJSC_Vol_15_Iss_2_Paper_4_3497_3504.pdf |
| Link text | Click here |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles Abstract Database |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Total Checkouts | Barcode | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | School of Engineering & Technology | School of Engineering & Technology | Archieval Section | 24/04/2025 | 2025-0660 | 24/04/2025 | 24/04/2025 | Articles Abstract Database |