Integrating Cryptographic Security Features in Information System Barcodes for Self-Service Systems

Integrating services in an information system is necessary to provide services that can optimize an information system. One of the systems in PKKMB activities that will be combined with information security features is the attendance system. This research uses the Liner Sequential Model (LSM) method to integrate the QR Code attendance system with security features. This research aims to integrate QR Codes by optimizing increased security by combining the Advanced Encryption Standard (AES) algorithm with base64 with a dynamic data model to complicate the QR Code manipulation process. Contribution This study makes optimization of the AES encryption model to improve data security on QR Code. Algorithm testing results include using a Character Error Rate (CER) of 0%, Avalanche Effect (AE) testing with a value of 53.05%, and response time (RT) testing of 10.26ms

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Publication Details

Journal
Advance Sustainable Science Engineering and Technology
Published
2024-09-20
DOI
https://doi.org/10.26877/asset.v6i4.850
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrating Cryptographic Security Features in Information System Barcodes for Self-Service Systems

Muhammad Najibulloh Muzaki, Aidina Ristyawan, Dwi Harini, Sucipto Sucipto et al.
Advance Sustainable Science Engineering and Technology
Advanced Malware Detection Techniques
article

Integrating Cryptographic Security Features in Information System Barcodes for Self-Service Systems

Muhammad Najibulloh Muzaki, Aidina Ristyawan, Dwi Harini, Sucipto Sucipto, Mohamed Naeem Antharathara Abdulnazar, Wahid Ibnu Zaman
article en

Abstract

Integrating services in an information system is necessary to provide services that can optimize an information system. One of the systems in PKKMB activities that will be combined with information security features is the attendance system. This research uses the Liner Sequential Model (LSM) method to integrate the QR Code attendance system with security features. This research aims to integrate QR Codes by optimizing increased security by combining the Advanced Encryption Standard (AES) algorithm with base64 with a dynamic data model to complicate the QR Code manipulation process. Contribution This study makes optimization of the AES encryption model to improve data security on QR Code. Algorithm testing results include using a Character Error Rate (CER) of 0%, Avalanche Effect (AE) testing with a value of 53.05%, and response time (RT) testing of 10.26ms

Advance Sustainable Science Engineering and TechnologyVol. 6(4)
Universitas Nusantara PGRI Kediri
Openalex Percentile: Top 83%
Advanced Malware Detection Techniques
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