1,487 research outputs found

    Hybrid chaotic map with L-shaped fractal Tromino for image encryption and decryption

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    Insecure communication in digital image security and image storing are considered as important challenges. Moreover, the existing approaches face problems related to improper security at the time of image encryption and decryption. In this research work, a wavelet environment is obtained by transforming the cover image utilizing integer wavelet transform (IWT) and hybrid discrete cosine transform (DCT) to completely prevent false errors. Then the proposed hybrid chaotic map with L-shaped fractal Tromino offers better security to maintain image secrecy by means of encryption and decryption. The proposed work uses fractal encryption with the combination of L-shaped Tromino theorem for enhancement of information hiding. The regions of L-shaped fractal Tromino are sensitive to variations, thus are embedded in the watermark based on a visual watermarking technique known as reversible watermarking. The experimental results showed that the proposed method obtained peak signal-to-noise ratio (PSNR) value of 56.82dB which is comparatively higher than the existing methods that are, Beddington, free, and Lawton (BFL) map with PSNR value of 8.10 dB, permutation substitution, and Boolean operation with PSNR value of 21.19 dB and deoxyribonucleic acid (DNA) level permutation-based logistic map with PSNR value of 21.27 dB

    ENKRIPSI CITRA DIGITAL MENGGUNAKAN KOMPOSISI TRANSPOSISI CAT MAP DAN SUBTITUSI KEY STREAM LOGISTIC MAP

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    Transmisi pertukaran data digital melalui jaringan internat menjadi hal penting pada kemajuan teknologi. Risiko pembajakan oleh pihak yang tidak bertanggung jawab mungkin terjadi karena kemudahan dalam pertukaran data. Pengembangan metode enkripsi data yang andal dan kuat adalah solusi untuk risiko ini. Penelitian ini mengusulkan algoritma enkripsi data baru melalui komposisi enkripsi transposisi Cat Map dan enkripsi substitusi Logistic Map. Algoritma yang diusulkan secara bersamaan mengubah posisi data dan mengubah nilai data secara acak. Penelitian telah dilakukan dengan menggunakan beberapa citra dengan berbagai fitur dan ukuran yang berbeda. Analisis keacakan citra hasil enkripsi menunjukkan bahwa histogram intensitas warna piksel memiliki distribusi yang seragam dengan nilai korelasi rendah mendekati 0. Hasil analisis peak signal to noise ratio (PSNR) menunjukkan citra hasil dekripsi sama dengan citra asli . Algoritma yang diusulkan memiliki ruang kunci 3.24 Ă— 1068. Hasil NPCR, UACI dan Entropi menunjukkan algoritma yang diusulkan tahan terhadap serangan diferensial dan serangan entropi

    A novel four-wing chaotic system with multiple equilibriums: Dynamical analysis, multistability, circuit simulation and pseudo random number generator (PRNG) based on the voice encryption

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    Recently, there has been tremendous interest worldwide in the possibility of using chaos in communication systems. Many different chaos-based secure communication schemes have been proposed up until now. However, systems with strong chaoticity are more suitable for chaos-based secure communication. From the viewpoint of Lyapunov exponents, a chaotic system with a larger positive Lyapunov exponent is said to be more complex. This paper constructing a multistable chaotic system that can produce coexisting attractors is an attractive field of research due to its theoretical and practical usefulness. An innovative 3D dynamical system is presented in this research. It can display various coexisting attractors for the same values of parameters. The new system is more suitable for chaos-based applications than recently reported systems since it exhibits strong multistable chaotic behavior, as proved by its large positive Lyapunov exponent. Furthermore, the accuracy of the numerical calculation and the system's physical implementations are confirmed by analog circuit simulation. Finally, implementing the proposed voice encryption is done using a four-wing chaotic system based on the PRNG

    Digitalization and Development

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    This book examines the diffusion of digitalization and Industry 4.0 technologies in Malaysia by focusing on the ecosystem critical for its expansion. The chapters examine the digital proliferation in major sectors of agriculture, manufacturing, e-commerce and services, as well as the intermediary organizations essential for the orderly performance of socioeconomic agents. The book incisively reviews policy instruments critical for the effective and orderly development of the embedding organizations, and the regulatory framework needed to quicken the appropriation of socioeconomic synergies from digitalization and Industry 4.0 technologies. It highlights the importance of collaboration between government, academic and industry partners, as well as makes key recommendations on how to encourage adoption of IR4.0 technologies in the short- and long-term. This book bridges the concepts and applications of digitalization and Industry 4.0 and will be a must-read for policy makers seeking to quicken the adoption of its technologies

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    IoT-based Secure Data Transmission Prediction using Deep Learning Model in Cloud Computing

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    The security of Internet of Things (IoT) networks has become highly significant due to the growing number of IoT devices and the rise in data transfer across cloud networks. Here, we propose Generative Adversarial Networks (GANs) method for predicting secure data transmission in IoT-based systems using cloud computing. We evaluated our model’s attainment on the UNSW-NB15 dataset and contrasted it with other machine-learning (ML) methods, comprising decision trees (DT), random forests, and support vector machines (SVM). The outcomes demonstrate that our suggested GANs model performed better than expected in terms of precision, recall, F1 score, and area under the receiver operating characteristic curve (AUC-ROC). The GANs model generates a 98.07% accuracy rate for the testing dataset with a precision score of 98.45%, a recall score of 98.19%, an F1 score of 98.32%, and an AUC-ROC value of 0.998. These outcomes show how well our suggested GANs model predicts secure data transmission in cloud-based IoT-based systems, which is a crucial step in guaranteeing the confidentiality of IoT networks

    SRSS: A New Chaos-Based Single-Round Single S-Box Image Encryption Scheme for Highly Auto-Correlated Data

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    With the advent of digital communication, securing digital images during transmission and storage has become a critical concern. The traditional s-box substitution methods often fail to effectively conceal the information within highly auto-correlated regions of an image. This paper addresses the security issues presented by three prevalent S-box substitution methods, i.e., single S-box, multiple S-boxes, and multiple rounds with multiple S-boxes, especially when handling images with highly auto-correlated pixels. To resolve the addressed security issues, this paper proposes a new scheme SRSS-the Single Round Single S-Box encryption scheme. SRSS uses a single S-box for substitution in just one round to break the pixel correlations and encrypt the plaintext image effectively. Additionally, this paper introduces a new Chaos-based Random Operation Selection System-CROSS, which nullifies the requirement for multiple S-boxes, thus reducing the encryption scheme's complexity. By randomly selecting the operation to be performed on each pixel, driven by a chaotic sequence, the proposed scheme effectively scrambles even high auto-correlation areas. When compared to the substitution methods mentioned above, the proposed encryption scheme exhibited exceptionally well in just a single round with a single S-box. The close-to-ideal statistical security analysis results, i.e., an entropy of 7.89 and a correlation coefficient of 0.007, validate the effectiveness of the proposed scheme. This research offers an innovative path forward for securing images in applications requiring low computational complexity and fast encryption and decryption speeds.Comment: 6 Page

    Sécurité des données de capteurs ambiants dans les habitats à l’aide d’autoencodeurs

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    Dans ce mémoire, nous visons à implémenter un prototype d’algorithme de cryptographie basé sur les réseaux de neurones. Dans le cadre des travaux sur la reconnaissance d’activités au sein d’habitats intelligents opérés par le LIARA (Laboratoire d’Intelligence Ambiante pour la Reconnaissance d’Activités), une attention est portée de plus en plus sur la protection de la vie privée des individus. En effet pendant longtemps, on a eu affaire à des données de capteurs simples comme les tapis de pressions, les détecteurs électromagnétiques, les détecteurs de mouvement. Comme ces données ne permettent pas d’avoir accès à des informations génériques basiques sur ce qui se déroulait au sein des murs des résidences suivies, l’aspect sécurité occupait une petite place dans les travaux. Dans le cadre d’un projet de déploiement à grande échelle de maisons intelligentes financé par MEDTEQ (le Consortium pancanadien de recherche industrielle et d’innovation en technologies médicales du Québec) et Age-Well (un réseau canadien visant à élaborer des technologies et des services pour le vieillissement en santé) notre équipe explore l’utilisation des réseaux de neurones pour sécuriser les données transmises entre les maisons intelligentes et les serveurs de traitement de données. Afin de bien comprendre nos besoins, il est important de poursuivre cette question cruciale en parallèle avec une étude du potentiel des réseaux de neurones pour remplacer la cryptographie traditionnelle dans l’encodage de données plus complexes. En effet, ces derniers temps, nous avons étudié des capteurs plus informatifs tels que les caméras thermiques, les caméras de profondeurs, les capteurs RFID et les radars à ultra large bande. Ces capteurs ont plus d’informations sur les activités qui se déroulent dans une résidence, mais ils impliquent une plus grande charge de traitement. En conséquence, il semble donc intéressant d’étudier la possibilité d’utiliser une architecture de réseau de neurones artificiels pour encoder localement les données et les décoder à distance afin d’augmenter la sécurité, de réduire les calculs supplémentaires et de diminuer la taille des données à transmettre. En somme, cette étude portera sur l’étude comparative de ces encodages au sein d’habitats intelligents et consistera à mettre en place un système d’encodage de données fonctionnel basé sur des autoencodeurs

    Image hiding in audio file using chaotic method

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    In this paper, we propose an efficient image hiding method that combines image encryption and chaotic mapping to introduce adaptive data hiding for improving the security and robustness of image data hiding in cover audio. The feasibility of using chaotic maps to hide encrypted image in the high frequency band of the audio is investigated. The proposed method was based on hiding the image data in the noisiest part of the audio, which is the high frequency band that was extracted by the zero crossing filter. Six types of digital images were used, each of size fit the length of used audio, this to facilitate the process of hiding them among the audio samples. The input image was encrypted by a one-time pad method, then its bits were hidden in the audio by the chaotic map. The process of retrieving the image from the audio was in the opposite way, where the image data was extracted from the high frequency band of the audio file, and then the extracted image was decrypted to produce the retrieved image. Four qualitative metrics were used to evaluate the hiding method in two paths: the first depends on comparing the retrieved image with the original image, while the second depends on comparing the audio containing the image data with the original audio once, and another time by comparing the cover audio with the original audio. The results of the quality metrics proved the efficiency of the proposed method, and it showed a slight and unnoticed effect between the research materials, which indicates the success of the hiding process and the validity of the research path
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