Skema Otentikasi Berbasis Elliptic Curve Cryptography (ECC) pada Jaringan IoT untuk Sistem Informasi Kesehatan

Rachmayanti, Alifina (2024) Skema Otentikasi Berbasis Elliptic Curve Cryptography (ECC) pada Jaringan IoT untuk Sistem Informasi Kesehatan. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Seiring dengan perkembangan teknologi, Internet of Things (IoT) telah menjadi komponen vital dalam Smart Healthcare. Namun, keamanan data menjadi kekhawatiran besar, terutama saat informasi kesehatan sensitif dikirim melalui jaringan IoT yang rentan terhadap serangan siber, seperti Man-in-the-Middle (MITM) dan brute force. Penelitian ini mengusulkan skema otentikasi berbasis Elliptic Curve Cryptography (ECC) yang mengintegrasikan Elliptic Curve Diffie-Hellman (ECDH) dan Advanced Encryption Standard (AES) untuk jaringan IoT dalam sistem informasi kesehatan. Algoritma ECC menawarkan keamanan tinggi dengan ukuran kunci lebih kecil dibandingkan RSA, menjadikannya cocok untuk perangkat IoT dengan keterbatasan sumber daya. Metodologi penelitian mencakup dua fase utama: registrasi dan otentikasi. Pada fase registrasi, setiap klien mendaftar dengan server rumah sakit. Pada fase otentikasi, server dan perangkat IoT menggunakan ECDH untuk menghasilkan shared key secara aman, yang kemudian digunakan dalam algoritma AES untuk mengenkripsi dan mendekripsi data otentikasi. Kombinasi AES dan ECC dipilih karena AES memberikan enkripsi simetris yang cepat dan efisien, sedangkan ECC menyediakan kunci enkripsi yang kuat dengan ukuran lebih kecil, yang cocok untuk perangkat IoT. Hasil pengujian menunjukkan bahwa sistem ini dapat melakukan otentikasi dengan efisiensi tinggi, dimana pembangkitan kunci ECC lebih cepat dibandingkan RSA. Proses enkripsi dan dekripsi data menggunakan AES-256 membutuhkan waktu masing-masing 0,08 ms dan 0,028 ms. Skema ini juga tahan terhadap serangan SQL injection dan brute force, menjaga kerahasiaan dan integritas data kesehatan serta melindungi dari serangan pihak ketiga.
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Along with technological advances, the Internet of Things (IoT) has become a vital component in Smart Healthcare. However, data security has become a major concern, especially when sensitive health information is sent through IoT networks that are vulnerable to cyber-attacks, such as Man-in-the-Middle (MITM) and brute force. The research proposes an Elliptic Curve Cryptography (ECC)-based authentication scheme that integrates the Elliptical Curve Diffie-Hellman (ECDH) and Advanced Encryption Standard (AES) for IoT networks in health information systems. ECC algorithms offer high security with smaller key sizes than RSAs, making them suitable for IoT devices with limited resources. The research methodology covers two main phases: registration and authentication. At the registration phase, each client logs into the hospital server. At the authentication stage, the server and IoT devices use ECDH to generate shared keys securely, which are then used in the AES algorithm to encrypt and decrypt authenticated data. The combination of AES and ECC is chosen because AES provides fast and efficient symmetrical encryption, while ECC provides a smaller-sized, powerful encryption key that is suitable for the IoT device. Test results show that the system can perform high-efficiency authentication, where the generation of ECC keys is faster than RSA. The AES-256 data encoding and decryption processes take 0,08 ms and 0,028 ms, respectively. The scheme is also resistant to SQL injection and brute force attacks, safeguards the confidentiality and integrity of health data, and protects against third-party attacks

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Authentication, Data Security, Elliptic Curve Cryptography (ECC), Internet of Things (IoT), Smart Healthcare, Eliptic Curve Cryptography (ECC), Internet of Things (IoT), Keamanan Data, Otentikasi, Smart Healthcare.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User:	Alifina Rachmayanti
Date Deposited:	30 Jul 2024 03:21
Last Modified:	30 Jul 2024 03:21
URI:	http://repository.its.ac.id/id/eprint/110213

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