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All Journal Jurnal Teknologi Informasi dan Multimedia Telcomatics
Yeovandi, Felix
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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Evaluasi Keamanan Sistem Autentikasi Biometrik pada Smartphone dan Rekomendasi Implementasi Optimal Yeovandi, Felix; Sabariman, Sabariman; Prasetyo, Stefanus Eko
JTIM : Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 1 (2025): February
Publisher : Puslitbang Sekawan Institute Nusa Tenggara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i1.653

Abstract

Biometric authentication on smartphones is a modern solution for more practical and secure login security. This technology offers advantages such as speed of access and resistance to forgery compared to password-based methods. However, there are various weaknesses, such as the potential for exploitation through malware, spoofing, or brute force attacks that exploit security holes, such as Cancel-After-Match-Fail (CAMF) and Match-After-Lock (MAL). Additionally, hacked biometric data cannot be replaced, leaving users vulnerable to long-term security threats. To overcome these weaknesses, this article recommends a security approach based on Trusted Execution Environment (TEE), AES-256 encryption, spoofing detection based on liveness recognition, anti-tamper mechanisms, and the application of rate limiting. The secure authentication flow implementation is designed to protect biometric data locally without transmission to external servers, ensuring user integrity and privacy is maintained. This flow includes suspicious activity detection, login encryption, and data protection with advanced encryption. Through a combination of these technologies, the biometric authentication system is characterized as being able to significantly maximize security by minimizing the risk of attacks on user data. This research provides evaluation results that the DNN deep neural network model trained with AES-256 is characterized as being able to produce accuracy above 99.9% with less than 5,000 power traces. Then, the implementation of liveness detection is characterized as being able to produce an F1-Score of 97.78% and an HTER of 8.47% in the intra-dataset scenario, as well as an F1-Score of 74.77% and an HTER of 29.05% in the cross-dataset scenario. This combination of technologies provides secure and efficient biometric authentication without compromising user comfort.
Perancangan Sistem Informasi MyPortal UIB Dengan Menggunakan Python dan MySQL Richard, Richard; Meriana, Angelina; Erick, Erick; Yeovandi, Felix; Hendra, Hendra
Telcomatics Vol. 8 No. 2 (2023)
Publisher : Universitas Internasional Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37253/telcomatics.v8i2.7370

Abstract

MyPortal merupakan suatu website yang bertujuan sebagai sarana bagi mahasiswa/i Universitas Internasional Batam dalam mencari informasi seputar perkuliahan. Tujuan penelitian ini adalah penulis mencoba merancang MyPortal sebagai aplikasi desktop yang dapat diakses baik secara online atau offline. Untuk merancang suatu aplikasi dibutuhkan sistem basis data yang mendukung, sehingga aplikasi dapat berjalan dengan optimal. Oleh karena itu penulis menggunakan MySQL sebagai database, serta beberapa panduan lain dalam mengerjakan proyek ini. Seperti ERD dan class diagram untuk memberikan penulis panduan dalam merelasikan obyek dan entitas. Sistem basis data membantu aplikasi dalam mengelola data-data yang saling berhubungan, sehingga dapat diakses dengan mudah oleh penggunanya, dan dapat digunakan banyak pengguna selagi masih dalam basis data yang sama. Selain memudahkan, penggunaan sistem basis data juga untuk menjaga keamanan dari data yang ada di dalamnya. Metodologi yang akan digunakan adalah Database System Development Life Cycle (DSDLC). Dengan metode ini, akan membantu mengembangkan sistem basis data selain itu menganalisis, dan merancang sistem basis data. Metode ini cocok untuk penelitian pada artikel ini.
Co-Authors Erick, Erick Hendra Hendra Meriana, Angelina Prasetyo, Stefanus Eko Richard Richard Sabariman Sabariman