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All Journal Jurnal Fitopatologi Indonesia Jurnal Amanat Agung Tematik : Jurnal Teknologi Informasi Komunikasi International Journal of Global Operations Research International Journal of Quantitative Research and Modeling Jurnal Agrisistem Jurnal Algoritma eProceedings of Engineering Medimuh : Jurnal Kesehatan Muhammadiyah Medimuh : Jurnal Kesehatan Muhammadiyah
Melina
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Religion Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Mathematics Medicine & Pharmacology Nursing Physics Public Health Veterinary

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Journal : International Journal of Quantitative Research and Modeling

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Cryptographic Security for Double Encryption on Images Using AES and IDEA Algorithms Nizar Septi maulana; Asep Id Hadiana; Melina
International Journal of Quantitative Research and Modeling Vol. 6 No. 3 (2025): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i3.1072

Abstract

Di era digital, keamanan citra rekam medis elektronik telah menjadi perhatian utama karena tingginya risiko kebocoran informasi sensitif. Studi ini menyelidiki dan mengembangkan implementasi enkripsi ganda pada data citra medis dengan menggabungkan Advanced Encryption Standard (AES) dan International Data Encryption Algorithm (IDEA) untuk meningkatkan keamanan citra, khususnya untuk citra rekam medis elektronik yang rentan terhadap pelanggaran informasi. AES digunakan karena efisiensinya dalam mengenkripsi data berukuran besar, sementara IDEA menawarkan struktur kunci yang kompleks yang memberikan perlindungan yang lebih kuat terhadap akses yang tidak sah. Kumpulan data citra Magnetic Resonance Imaging (MRI) yang diperoleh dari platform publik Kaggle digunakan sebagai objek uji untuk proses enkripsi dan dekripsi. Evaluasi dilakukan dengan menggunakan dua pendekatan utama: uji efek avalanche untuk mengukur sensitivitas perubahan input terhadap output ciphertext, dan uji waktu pemrosesan untuk menilai efisiensi kinerja enkripsi dan dekripsi. Hasilnya menunjukkan nilai rata-rata efek avalanche mencapai 49,97%, sangat mendekati nilai ideal 50%, menunjukkan tingkat difusi data yang tinggi dan kekuatan kriptografi yang kuat. Sementara itu, pengujian waktu enkripsi pada lima berkas citra menunjukkan bahwa rata-rata waktu yang dibutuhkan untuk melakukan enkripsi ganda menggunakan AES dan IDEA adalah 52,06 detik, dengan rentang waktu antara 42,0 detik hingga 63,5 detik, tergantung pada ukuran dan kompleksitas citra. Oleh karena itu, kombinasi AES dan IDEA terbukti meningkatkan kekuatan kriptografi tanpa mengurangi efisiensi operasional secara signifikan. Pendekatan enkripsi ganda ini dinilai layak dan efektif untuk diimplementasikan dalam sistem informasi kesehatan, terutama untuk menjaga kerahasiaan, integritas, dan keaslian citra rekam medis elektronik. Kata kunci: Enkripsi ganda, AES, IDEA, efek longsor, keamanan citra medis, efisiensi waktu pemrosesan
Digital Image Security with AES and Blowfish Double Encryption Iqbal Dwi Nulhakim; Asep Id Hadiana; Melina
International Journal of Quantitative Research and Modeling Vol. 6 No. 3 (2025): International Journal of Quantitative Research and Modeling (IJQRM)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i3.1073

Abstract

Protection of digital images is becoming increasingly important with the growing use of images as a medium of information in various fields, particularly in the healthcare sector. Medical images such as Magnetic Resonance Imaging (MRI) contain sensitive information that requires extra security against unauthorized access and data manipulation. This study aims to design and build a digital image security system using a dual encryption approach and authenticity verification based on watermarking. The security process is carried out in two main stages. First, images with text-based watermarks are encrypted using the Advanced Encryption Standard (AES) algorithm to protect their visual content. Second, the AES key is re-encrypted using the Blowfish algorithm to prevent the key from being stored in plaintext, thereby creating an additional layer of protection. The watermark is embedded into the image using the Singular Value Decomposition (SVD) method and is first converted into a hash value using the SHA-256 algorithm, which serves to verify the integrity of the image after decryption. The testing was conducted using the public dataset “Brain Tumor Image Dataset (Semantic Segmentation)” from Kaggle, which consists of brain MRI images in .jpg and .png formats. The system evaluation encompassed functionality, data security, and process efficiency through system function testing, measurement of encrypted data randomness (entropy test), file penetration using OpenSSL, and performance analysis in terms of processing time and file size. The research results show that the system successfully implemented double encryption with a high entropy level (approaching 8.00) and resistance to penetration attacks. In terms of efficiency, the system achieved an average encryption time of 81.35 ms and decryption time of 13.68 ms with minimal file size increase. Integrity testing confirmed that the SVD-SHA256-based watermark remained intact after the encryption-decryption process, enabling verification of image authenticity. The developed system efficiently maintains the confidentiality and authenticity of digital images and can be applied in electronic medical record systems or sensitive digital archives. Keywords: Digital images, double encryption, AES, Blowfish, SVD
Co-Authors Adam Firmansyah Suhendar apriliyanti mugianto putri, ira dwi Azurah, Nur Baharuddin Patandjengi Bongga Arifwidodo Busthanul, Nurabaya Firdaus, Syahrul Hadiana, Asep Id Iqbal Dwi Nulhakim Iqbal Maulana Jafaruddin Gusti Amri Ginting Julian Evan Chrisnanto Lestari, Abdila Muhammad Azrai, Muhammad Mustika Tuwo, Mustika Nida Ulhasanah Nizar Septi maulana Nur Hardina Rahmawati, A Lusi Fitri Rahmawati, Firda Salsabila, Mira Suharyani, Ine Tutik Kuswinanti Wina Witanti Wina Witanti Yulison Herry Chrisnanto