Design a Compact Non-linear S-Box with Multiple-Affine Transformations

Dawood, Omar A.; Khalaf, Mohammed; Mohammed, Falath M.; Almulla, Hussein

doi:10.1007/978-3-030-38752-5_34

Cited by 3 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The evaluation of E-ART have been done in a similar way adopted in different recent and relevant studies of cryptographic algorithms [14,23,25,39]. To evaluate its performance and efficiency, the proposed algorithm was implemented on the Java platform using NetBeans 8.2 and compared to AES-128 and DES.…”

Section: Experimental Evaluationmentioning

confidence: 99%

E-ART: A New Encryption Algorithm Based on the Reflection of Binary Search Tree

2021

View full text Add to dashboard Cite

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.

show abstract

Section: Experimental Evaluationmentioning

confidence: 99%