An encryption and decryption of phonetic alphabets using signed graphs
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.spl-2.33Keywords:
Encryption, Decryption, Signed Graph, Eigenvalues, EigenvectorsDimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Indeed, in signed graphs, the weights on the edges can be both positive and negative; this will provide a solid representation and manipulation framework for complicated relationships among phonetic symbols. Encryption and decryption of phonetic alphabets pose a number of special challenges and opportunities. This paper introduces a novel approach utilizing the eigenvalues and eigenvectors of signed graphs to develop more secure and efficient methods of encoding phonetic alphabets. Presented is a new cryptographic scheme; consider a mapping from phonetic alphabets onto a signed graph. Encryption should be carried out by means of structure-changing transformations of the latter, which leave intact the integrity of the information encoded. This approach allows for secure, invertible transformations to resist typical cryptographic attacks. Here, the decryption algorithm restores the encrypted graph back to the original phonetic symbols by systematically going through steps opposite to that taken during encryption. The proposal of signed graphs in the processes of phonetic alphabet encryption and decryption opens new frontiers of cryptographic practices, which have useful implications for secure communication systems and data protection.Abstract
How to Cite
Downloads
Similar Articles
- Annalakshmi D., C. Jayanthi, An asymmetric key encryption and decryption model incorporating optimization techniques for enhanced security and efficiency , The Scientific Temper: Vol. 15 No. 03 (2024): The Scientific Temper
- Priya Nandhagopal, Jayasimman Lawrence, ECE cipher: Enhanced convergent encryption for securing and deduplicating public cloud data , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- Krupali Bhatt, Tushharkumar Bhatt, Certain findings on the gamma graph of some graphs , The Scientific Temper: Vol. 15 No. spl-2 (2024): The Scientific Temper
- Aruljothi Rajasekaran, Jemima Priyadarsini R., ECDS: Enhanced Cloud Data Security Technique to Protect Data Being Stored in Cloud Infrastructure , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Rudrapati Bhuvaneswara Prasad, Avutala Mallikarjuna Reddy, Edge properties of lexicographic product graphs of open neighborhood graphs , The Scientific Temper: Vol. 16 No. 01 (2025): The Scientific Temper
- J. M. Aslam, K. M. Kumar, Enhancing cloud data security: User-centric approaches and advanced mechanisms , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- R. Prabhu, P. Archana, S. Anusooya, P. Anuradha, Improved Steganography for IoT Network Node Data Security Promoting Secure Data Transmission using Generative Adversarial Networks , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Priscilla I, Jayasimman Lawrence, Enhanced Symmetric Cryptography Technique (ESCTGPU) for Secure Communication between the IoT Gateway and the public Cloud Environment , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
- Milindkumar N. Dandale, Amar P. Yadav, P. S. K. Reddy, Seema G. Kadu, Madhusudana T, Manthan S. Manavadaria, Deep learning enhanced drug discovery for novel biomaterials in regenerative medicine utilizing graph neural network approach for predicting cellular responses , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Amudavalli L, K. Muthuramalingam, Integrated energy-efficient routing and secure data management for location-aware wireless sensor networks with PFO leveraged improved fuzzy unequal clustering algorithm (IFUC) , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
You may also start an advanced similarity search for this article.

