Abstract:Security of a recently proposed bitwise block cipher GIFT is evaluated in this paper. In order to mount full round attacks on the cipher, biclique cryptanalysis method is applied. Both variants of the block cipher are attacked using Independent biclique approach. For recovering the secret keys of GIFT-64, the proposed attack requires 2127.45 full GIFT-64 encryption and 28 chosen plain texts. For recovering the secret keys of GIFT-128, the proposed attack requires 2127.82 full GIFT-128 encryption and 218 chosen… Show more
“…− Related-key attacks: These attacks leverage similarities in the key schedules of different ciphers to break one cipher and then attack others. The recent proposal of the Biclique cryptanalysis technique has shown promise in exploiting related-key relationships in some block ciphers, raising concerns about potential vulnerabilities in cipher families [38]. − Algebraic attacks: These attacks utilize algebraic properties of the cipher's S-boxes or round functions to find weaknesses.…”
The increasing number of internet of things (IoT) devices, wearable technologies, and embedded systems has experienced a significant increase in recent years. This surge has brought attention to the necessity for cryptographic algorithms that are lightweight and capable of providing security in resource-constrained environments. The primary objective of lightweight block ciphers is to provide encryption capabilities with minimal computational overhead and decreased power consumption. As a result, they are particularly well-suited for use on devices that have limited resources. At the same time, machine learning methodologies have evolved into powerful mechanisms for the purposes of prediction, categorization, and system optimization. This study introduces a challenges and issues involved in integrating machine learning techniques with the development of lightweight block ciphers.
“…− Related-key attacks: These attacks leverage similarities in the key schedules of different ciphers to break one cipher and then attack others. The recent proposal of the Biclique cryptanalysis technique has shown promise in exploiting related-key relationships in some block ciphers, raising concerns about potential vulnerabilities in cipher families [38]. − Algebraic attacks: These attacks utilize algebraic properties of the cipher's S-boxes or round functions to find weaknesses.…”
The increasing number of internet of things (IoT) devices, wearable technologies, and embedded systems has experienced a significant increase in recent years. This surge has brought attention to the necessity for cryptographic algorithms that are lightweight and capable of providing security in resource-constrained environments. The primary objective of lightweight block ciphers is to provide encryption capabilities with minimal computational overhead and decreased power consumption. As a result, they are particularly well-suited for use on devices that have limited resources. At the same time, machine learning methodologies have evolved into powerful mechanisms for the purposes of prediction, categorization, and system optimization. This study introduces a challenges and issues involved in integrating machine learning techniques with the development of lightweight block ciphers.
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