An Innovative Multi-Party Authentication and Cyber Attacks Prevention Technique to Enhance the Security on Key and Data Transformation
Year: 2026
Type: article
Abstract: The increasing reliance on online infrastructure and the expansion of distributed network systems have made digital communication that is an indispensable part of modern life. However, this dependence has also attracted malicious attackers’ intent on intrusion, eavesdropping and compromising the security of sensitive information. This work presents an innovative approach to enhance the security in key generation, distribution and data transformation by developing a robust multi-party authentication technique. The work proposed a Modified Elliptic Curve Cryptography (MECC) technique to enhance the security for the key. The suggested approach leverages a combination of classical cryptography methods and innovative cyber attack prevention strategies to protect against unauthorized access and malicious threats. Additionally, the work introduces a novel encryption and decryption methodology for the secure transformation of key and data files using the MECC technique. Furthermore, a comparative analysis is conducted that benchmarks the performance of the proposed methodology against the traditional Elliptic Curve Cryptography (ECC) methodology. Experimental results show that MECC achieves encryption times ranging from 120.00 to 1376.99 seconds for files sized 10 to 100 MB. It is offering up to 28% faster performance and enhanced resistance to cryptographic attacks compared to traditional ECC. The applications of the suggested methodology are particularly suitable for E-banking systems that demand secure communication and real-time transactions. Furthermore, this work explores security defense strategies against Local File Inclusion (LFI) attacks in the financial sector, reinforcing the resilience of digital systems against emerging cyber threats.
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $500
OpenAlex ID: W7139997474