Development of a Multi-Layered Authentication System

To acknowledge the growing need for cybersecurity in the digital era, this paper presents the development of a Secure Digit Authentication System (SDAS), designed to enhance security in the field of financial transactions. The core innovation of SDAS is multi-layered authentication using a machine learning-based handwritten digit recognition model. This system addresses the vulnerabilities in the existing conventional methods and ensures robustness against automated attacks. SDAS consists of four key components: user authentication through hashed passwords, account number verification, unique code authentication using handwritten digit recognition, and a balance-checking module. The procedure combines cryptographic password protection with machine learning models trained on digit recognition to enhance transaction security.

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Publication Details

Published
2024-11-21
DOI
https://doi.org/10.1109/delcon64804.2024.10866605
Primary Topic
User Authentication and Security Systems
Type
article
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article

Development of a Multi-Layered Authentication System

Preetvanti Singh, Surat Satsangi
User Authentication and Security Systems
article

Development of a Multi-Layered Authentication System

Preetvanti Singh, Surat Satsangi
article en

Abstract

To acknowledge the growing need for cybersecurity in the digital era, this paper presents the development of a Secure Digit Authentication System (SDAS), designed to enhance security in the field of financial transactions. The core innovation of SDAS is multi-layered authentication using a machine learning-based handwritten digit recognition model. This system addresses the vulnerabilities in the existing conventional methods and ensures robustness against automated attacks. SDAS consists of four key components: user authentication through hashed passwords, account number verification, unique code authentication using handwritten digit recognition, and a balance-checking module. The procedure combines cryptographic password protection with machine learning models trained on digit recognition to enhance transaction security.

Dayalbagh Educational Institute (IN)
Openalex Percentile: Top 57%
User Authentication and Security Systems
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