Enkripsi Citra Berbasis Plaintext-Related Logistic Map dengan Optimasi Parameter Plaintext Menggunakan Hippopotamus Optimization

Firmansah, Mochamad Davit (2026) Enkripsi Citra Berbasis Plaintext-Related Logistic Map dengan Optimasi Parameter Plaintext Menggunakan Hippopotamus Optimization. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Keamanan citra digital penting untuk melindungi data visual sensitif. Penelitian ini mengkaji enkripsi citra RGB berbasis plaintext-related logistic map dengan optimasi parameter menggunakan Hippopotamus Optimization (HO). Optimasi bertujuan memperoleh parameter per-image yang adaptif, tetap valid pada wilayah chaos, menekan korelasi piksel, mempertahankan keacakan cipher-image, dan menjamin dekripsi deterministik. Proses penelitian meliputi persiapan 90 citra RGB KADID-10k berdasarkan kategori DMOS, enkripsi-dekripsi baseline, optimasi parameter $X = [r_{\min}, \varepsilon, T_0, Q]$, enkripsi-dekripsi menggunakan parameter HO, serta evaluasi hasil. Skema enkripsi terdiri atas key processing, image rearrangement, plaintext-related encryption, pembangkitan dan kuantisasi deret chaos, confusion, diffusion, dan key whitening, sedangkan dekripsi dilakukan melalui operasi inversnya. Evaluasi menggunakan entropi, korelasi piksel bertetangga, NPCR, UACI, sensitivitas kunci, waktu komputasi, validasi dekripsi, dan histogram. Hasil pengujian menunjukkan seluruh citra berhasil didekripsi secara deterministik. Entropi baseline dan HO sama-sama mendekati nilai ideal 8, yaitu 7.999064 dan 7.999060. Rata-rata korelasi turun dari 0.000975 menjadi 0.000403. NPCR dan UACI hasil optimasi tetap tinggi, yaitu 99.131889% dan 33.458340%. Sensitivitas kunci menghasilkan NPCR 99.61565% dan UACI 33.47159%, serta dekripsi dengan kunci salah gagal mengembalikan citra asli. Median waktu enkripsi-dekripsi turun dari sekitar 0.44 detik menjadi 0.42 detik, dengan biaya pencarian HO sekitar 536 detik. Secara keseluruhan, HO efektif menghasilkan parameter adaptif dan menjaga keamanan skema.
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The security of digital images is essential for protecting sensitive visual data. This study investigates RGB image encryption based on a plaintext-related logistic map with parameter optimization using Hippopotamus Optimization (HO). The optimization aims to obtain adaptive per-image parameters, keep them valid in the chaotic region, reduce adjacent-pixel correlation, preserve ciphertext randomness, and ensure deterministic decryption. The research process includes preparing 90 RGB images from the KADID-10k dataset based on DMOS categories, performing baseline encryption-decryption, optimizing $X = [r_{\min}, \varepsilon, T_0, Q]$, applying HO-based encryption-decryption, and evaluating the results. The encryption scheme consists of key processing, image rearrangement, plaintext-related encryption, chaotic sequence generation and quantization, confusion, diffusion, and key whitening, while decryption is performed through the inverse operations. The evaluation uses entropy, adjacent-pixel correlation, NPCR, UACI, key sensitivity, computational time, deterministic validation, and histogram analysis. The results show that all images were successfully decrypted in a deterministic manner. The entropy values of the baseline and HO schemes were both close to the ideal value of 8, namely 7.999064 and 7.999060. The average correlation decreased from 0.000975 to 0.000403. The optimized NPCR and UACI remained high at 99.131889% and 33.458340%. Key sensitivity testing produced an NPCR of 99.61565% and a UACI of 33.47159%, while decryption using an incorrect key failed to recover the original image. The median encryption-decryption time decreased from about 0.44 seconds to 0.42 seconds, with an HO search cost of about 536 seconds. Overall, HO effectively generates adaptive parameters while maintaining the scheme security.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	enkripsi citra, logistic map, plaintext-related, Hippopotamus Optimization, citra RGB, metrik keamanan, image encryption, logistic map, plaintext-related, Hippopotamus Optimization, RGB image, security metrics.
Subjects:	Q Science > QA Mathematics > QA76.9.A25 Computer security. Digital forensic. Data encryption (Computer science) T Technology > T Technology (General) > T57.84 Heuristic algorithms. T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques. Image analysis--Data processing. T Technology > TH Building construction > TH9737 Electronic security systems T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5102.94 Cryptographic techniques
Divisions:	Faculty of Mathematics and Science > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Mochamad Davit Firmansah
Date Deposited:	28 Jul 2026 02:18
Last Modified:	28 Jul 2026 02:18
URI:	http://repository.its.ac.id/id/eprint/138262

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