Kompresi Dan Enkripsi Gambar Medis Dengan Menggunakan Discrete Cosine Transform, Arithmetic Encoding, dan Chaos-Based Encryption

Afandi, Tiffany Maliati Khumairoh (2021) Kompresi Dan Enkripsi Gambar Medis Dengan Menggunakan Discrete Cosine Transform, Arithmetic Encoding, dan Chaos-Based Encryption. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penggunaan rekam kesehatan elektronik dapat mempermudah akses ke rekam kesehatan di mana saja. Dokter, agen asuransi, perawat, dan pasien dapat mengaksesnya melalui internet. Tetapi, kemudahan tersebut memiliki kelemahan bahwa data pasien yang telah terdigitalisasi dapat disimpan melalui banyak media, termasuk personal device, thumb drive, maupun cloud-based storage yang mana media-media tersebut riskan dengan serangan cyber dan dapat diakses oleh orang yang tidak bertanggung jawab. Dari permasalahan-permasalahan tersebut dibutuhkan sistem dengan metode kompresi dan enkripsi agar data medis dapat ditransmisi dengan mudah, cepat, dan aman. Penulis mengusulkan enkripsi berbasis Chaos dikombinasikan dengan Arithmetic Encoding dan Discrete Cosine Transform (DCT) untuk kompresi. Pertama, gambar medis dikompres dengan menggunakan DCT. Kemudian, gambar tersebut dikompres lagi dengan teknik pengkodean aritmatika. Setelah itu, file Hasil kompresi dienkripsi dengan menggunakan dua chaotic sequence berfungsi untuk mengacak file.
Dari metode yang diusulkan menghasilkan rasio kompresi sebesar 77,15 %, PSNR sebesar 42,49 dB, dan kecepatan (waktu pemrosesan) sebesar 27,31 s. Hasil tersebut menunjukkan bahwa gambar yang terkompresi memiliki kualitas bagus dan efektif karena nilai PSNR di atas 30 dB dan rasio kompresi di bawah 100% serta membutuhkan waktu pemrosesan relatif cepat. Metode ini juga lolos dalam pengujian NIST yang membuktikan bahwa data telah teracak dalam proses enkripsi.
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The use of electronic medical records can facilitate access to medical
records anywhere. Doctors, insurance agents, nurses, and patients can access it via
the internet. However, this convenience has the disadvantage that digitalized
patient data can be stored through many media, including personal devices, thumb
drives, and cloud-based storage where these media are at risk of cyber attacks and
can be accessed by the person responsible. From these problems, a system with
compression and encryption methods is needed so that medical data can be
transmitted easily, quickly and safely. The author proposes a Chaos-based
encryption combined with Arithmetic Encoding and Discrete Cosine Transform
(DCT) for compression. First, medical images are compressed using DCT. Then,
the image is compressed again using the arithmetic encoding technique. After that,
the compressed file is encrypted using two chaotic sequences to randomize the files.
The proposed method resulting a compression ratio of 77.15%, a PSNR of
42.49 dB, and a processing time of 27.31 s. These results indicate that the
compressed image has good quality and effective because the PSNR value is above
30 dB, the compression ratio is below 100%, which means the compressed and
encryption file size is less than the original, and takes time relatively fast. This
method also passed the NIST test which proves that the data has been randomized
in the encryption process.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	chaotic function, DCT, enkripsi, gambar medis, kompresi, chaotic function, compression, discrete cosine transform, encryption, medical images
Subjects:	Q Science > QA Mathematics > QA76.9.A25 Computer security. Digital forensic. Data encryption (Computer science) T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5105 Data Transmission Systems 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:	Tiffany Maliati Khumairoh Afandi
Date Deposited:	26 Feb 2021 05:27
Last Modified:	26 Feb 2021 05:29
URI:	http://repository.its.ac.id/id/eprint/82914

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