Abstract
Data security has become crucial to most enterprise and government applications due to the increasing amount of data generated, collected, and analyzed. Many algorithms have been developed to secure data storage and transmission. However, most existing solutions require multi-round functions to prevent differential and linear attacks. This results in longer execution times and greater memory consumption, which are not suitable for large datasets or delay-sensitive systems. To address these issues, this work proposes a novel algorithm that uses, on one hand, the reflection property of a balanced binary search tree data structure to minimize the overhead, and on the other hand, a dynamic offset to achieve a high security level. The performance and security of the proposed algorithm were compared to Advanced Encryption Standard and Data Encryption Standard symmetric encryption algorithms. The proposed algorithm achieved the lowest running time with comparable memory usage and satisfied the avalanche effect criterion with 50.1%. Furthermore, the randomness of the dynamic offset passed a series of National Institute of Standards and Technology (NIST) statistical tests.
Highlights
The emergence of social media platforms and smartphone applications has resulted in the generation of vast volumes of data, referred to as “big data.” Big data is defined as massive and diverse datasets that exceed the computational, storage, and communication capabilities of traditional methods or systems [1]
Our avalanche effect analysis showed that E-ART changed on average half of the bits in the ciphertext when a single bit was changed in the initial keys, demonstrating that it is sufficiently sensitive to any change in the key, making keyrelated attacks considerably more difficult to succeed
The Bit Independence Criterion (BIC) analysis performed on two avalanche variables showed a satisfactory bit independence criterion as the correlation value obtained was close to 0
Summary
The emergence of social media platforms and smartphone applications has resulted in the generation of vast volumes of data, referred to as “big data.” Big data is defined as massive and diverse datasets that exceed the computational, storage, and communication capabilities of traditional methods or systems [1]. Big data is defined as massive and diverse datasets that exceed the computational, storage, and communication capabilities of traditional methods or systems [1]. These data are used for further analysis to provide insights into applications related to domains such as healthcare, banking, and finance. Cryptography is the ancient practice of securing data for transmission and storage It is a set of processes or functions using keys to encrypt plain text so that only those for whom it is intended can read and process it. Plaintext characters are shifted depending on a given mapping key [10] These ciphers are highly susceptible to a cryptanalysis attack [11]. Aung and Hal [15] combined a Vigenère cipher with an Affine cipher to increase the level diffusion and confusion properties
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