39 research outputs found

    COMPARATIVE STUDY OF CHAOTIC SYSTEM FOR ENCRYPTION

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    Chaotic systems leverage their inherent complexity and unpredictability to generate cryptographic keys, enhancing the security of encryption algorithms. This paper presents a comparative study of 13 chaotic keymaps. Several evaluation metrics, including keyspace size, dimensions, entropy, statistical properties, sensitivity to initial conditions, security level, practical implementation, and adaptability to cloud computing, are utilized to compare the keymaps. Keymaps such as Logistic, Lorenz, and Henon demonstrate robustness and high-security levels, offering large key space sizes and resistance to attacks. Their efficient implementation in a cloud computing environment further validates their suitability for real-world encryption scenarios. The context of the study focuses on the role of the key in encryption and provides a brief specification of each map to assess the effectiveness, security, and suitability of the popular chaotic keymaps for encryption applications. The study also discusses the security assessment of resistance to the popular cryptographic attacks: brute force, known plaintext, chosen plaintext, and side channel. The findings of this comparison reveal the Lorenz Map is the best for the cloud environment based on a specific scenario

    Security Analysis of a Color Image Encryption Scheme Based on Dynamic Substitution and Diffusion Operations

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    In 2019, Essaid et al. proposed an encryption scheme for color images based on chaotic maps. Their solution uses two enhanced chaotic maps to dynamically generate the secret substitution boxes and the key bytes used by the cryptosystem. Note that both types of parameters are dependent on the size of the original image. The authors claim that their proposal provides enough security for transmitting color images over unsecured channels. Unfortunately, this is not the case. In this paper, we introduce two cryptanalytic attacks for Essaid et al.\u27s encryption scheme. The first one is a chosen plaintext attack, which for a given size, requires 256256 chosen plaintexts to allow an attacker to decrypt any image of this size. The second attack is a a chosen ciphertext attack, which compared to the first one, requires 512512 chosen ciphertexts to break the scheme for a given size. These attacks are possible because the generated substitution boxes and key bits remain unchanged for different plaintext images

    Distinguishing Lightweight Block Ciphers in Encrypted Images

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    Modern day lightweight block ciphers provide powerful encryption methods for securing IoT communication data. Tiny digital devices exchange private data which the individual users might not be willing to get disclosed. On the other hand, the adversaries try their level best to capture this private data. The first step towards this is to identify the encryption scheme. This work is an effort to construct a distinguisher to identify the cipher used in encrypting the traffic data. We try to establish a deep learning based method to identify the encryption scheme used from a set of three lightweight block ciphers viz. LBlock, PRESENT and SPECK. We make use of images from MNIST and fashion MNIST data sets for establishing the cryptographic distinguisher. Our results show that the overall classification accuracy depends firstly on the type of key used in encryption and secondly on how frequently the pixel values change in original input image

    Security Analysis of a Color Image Encryption Scheme Based on a Fractional‑Order Hyperchaotic System

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    In 2022, Hosny et al. introduce an image encryption scheme that employs a fractional-order chaotic system. Their approach uses the hyper-chaotic system to generate the system\u27s main parameter, namely a secret permutation which is dependent on the size and the sum of the pixels of the source image. According to the authors, their scheme offers adequate security (i.e. 498498 bits) for transmitting color images over unsecured channels. Nevertheless, in this paper we show that the scheme\u27s security is independent on the secret parameters used to initialize the hyper-chaotic system. More precisely, we provide a brute-force attack whose complexity is O(210.57(WH)3)\mathcal O(2^{10.57}(WH)^3) and needs 29.57WH2^{9.57}WH oracle queries, where WW and HH are the width and the height of the encrypted image. For example, for an image of size 4000×300004000 \times 30000 (1212 megapixels image) we obtain a security margin of 81.1181.11 bits, which is six times lower than the claimed bound. To achieve this result, we present two cryptanalytic attacks, namely a chosen plaintext attack and a chosen ciphertext attack

    COMPARATIVE STUDY OF CHAOTIC SYSTEM FOR ENCRYPTION

    Get PDF
    Chaotic systems leverage their inherent complexity and unpredictability to generate cryptographic keys, enhancing the security of encryption algorithms. This paper presents a comparative study of 13 chaotic keymaps. Several evaluation metrics, including keyspace size, dimensions, entropy, statistical properties, sensitivity to initial conditions, security level, practical implementation, and adaptability to cloud computing, are utilized to compare the keymaps. Keymaps such as Logistic, Lorenz, and Henon demonstrate robustness and high-security levels, offering large key space sizes and resistance to attacks. Their efficient implementation in a cloud computing environment further validates their suitability for real-world encryption scenarios. The context of the study focuses on the role of the key in encryption and provides a brief specification of each map to assess the effectiveness, security, and suitability of the popular chaotic keymaps for encryption applications. The study also discusses the security assessment of resistance to the popular cryptographic attacks: brute force, known plaintext, chosen plaintext, and side channel. The findings of this comparison reveal the Lorenz Map is the best for the cloud environment based on a specific scenario

    Entropy in Image Analysis III

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    Image analysis can be applied to rich and assorted scenarios; therefore, the aim of this recent research field is not only to mimic the human vision system. Image analysis is the main methods that computers are using today, and there is body of knowledge that they will be able to manage in a totally unsupervised manner in future, thanks to their artificial intelligence. The articles published in the book clearly show such a future

    Entropy in Image Analysis II

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    Image analysis is a fundamental task for any application where extracting information from images is required. The analysis requires highly sophisticated numerical and analytical methods, particularly for those applications in medicine, security, and other fields where the results of the processing consist of data of vital importance. This fact is evident from all the articles composing the Special Issue "Entropy in Image Analysis II", in which the authors used widely tested methods to verify their results. In the process of reading the present volume, the reader will appreciate the richness of their methods and applications, in particular for medical imaging and image security, and a remarkable cross-fertilization among the proposed research areas
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