Digital Image Encryption Using Logistic Map
Dublin Core
Title
Digital Image Encryption Using Logistic Map
Subject
logistic map; digital image encryption; python
Description
This study focuses on the application of the Logistic Map algorithm in Python programming language for Digital Image
Encryption and Decryption, the differentiating aspect of the present research in contrast to prior studies lies in its elucidation
of the practical application of the Logistic Map within the Python programming language, as opposed to the antecedent
investigations which primarily confined their discourse to the realm of scientific and mathematical abstraction. Not only that,
but it also investigates the impact of image type, image size, and Logistic Map parameter values on computational speed,
memory usage, Encryption and Decryption results. Three image sizes (300px x 300px, 500px x 500px, and 1024px x 1024px)
in TIFF, JPG, and PNG formats are considered. The Digital Image Encryption and Decryption process utilizes the Logistic
Map algorithm implemented in Python. Various parameter values are tested for each image type and size to analyze the
Encryption and Decryption outcomes. This research has effectively implemented the logistic map algorithm, resulting in the
discovery of several significant findings. The findings indicate that image type does not affect memory usage, which remains
consistent regardless of image type. However, image type significantly influences Decryption results and computation time.
Notably, the TIFF image type exhibits the fastest computation time, with durations of 0.17188 seconds, 0.28125 seconds, and
1.10938 seconds for 300px x 300px, 500px x 500px, and 1024px x 1024px images, respectively. Additionally, the Decryption
results vary depending on the image type. The Logistic Map algorithm is unable to restore Encryption results accurately for
JPG images. Furthermore, this research highlights those higher values of x, Mu, and Chaos result in narrower histogram
values, resulting in better encryption results, as evidenced by experiments using x=0.102, Mu=3.9 and Chaos=6400. This study
contributes to the field by exploring the application of the Logistic Map algorithm in Python and analyzing the effects of image
type, image size, and Logistic Map parameter values on computation time, memory usage, and Digital Image Encryption and
Decryption results.
Encryption and Decryption, the differentiating aspect of the present research in contrast to prior studies lies in its elucidation
of the practical application of the Logistic Map within the Python programming language, as opposed to the antecedent
investigations which primarily confined their discourse to the realm of scientific and mathematical abstraction. Not only that,
but it also investigates the impact of image type, image size, and Logistic Map parameter values on computational speed,
memory usage, Encryption and Decryption results. Three image sizes (300px x 300px, 500px x 500px, and 1024px x 1024px)
in TIFF, JPG, and PNG formats are considered. The Digital Image Encryption and Decryption process utilizes the Logistic
Map algorithm implemented in Python. Various parameter values are tested for each image type and size to analyze the
Encryption and Decryption outcomes. This research has effectively implemented the logistic map algorithm, resulting in the
discovery of several significant findings. The findings indicate that image type does not affect memory usage, which remains
consistent regardless of image type. However, image type significantly influences Decryption results and computation time.
Notably, the TIFF image type exhibits the fastest computation time, with durations of 0.17188 seconds, 0.28125 seconds, and
1.10938 seconds for 300px x 300px, 500px x 500px, and 1024px x 1024px images, respectively. Additionally, the Decryption
results vary depending on the image type. The Logistic Map algorithm is unable to restore Encryption results accurately for
JPG images. Furthermore, this research highlights those higher values of x, Mu, and Chaos result in narrower histogram
values, resulting in better encryption results, as evidenced by experiments using x=0.102, Mu=3.9 and Chaos=6400. This study
contributes to the field by exploring the application of the Logistic Map algorithm in Python and analyzing the effects of image
type, image size, and Logistic Map parameter values on computation time, memory usage, and Digital Image Encryption and
Decryption results.
Creator
Muhammad Rizki, Erik Iman Heri Ujianto, Rianto
Source
http://jurnal.iaii.or.id
Publisher
Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association
Date
December 2023
Contributor
Sri Wahyuni
Rights
ISSN Media Electronic: 2580-0760
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Muhammad Rizki, Erik Iman Heri Ujianto, Rianto, “Digital Image Encryption Using Logistic Map,” Repository Horizon University Indonesia, accessed February 4, 2026, https://repository.horizon.ac.id/items/show/10152.