Using the Muthavhine Function to Modify Skipjack Algorithm to Prevent LC and DC Attacks on IoT Devices

The Skipjack algorithm is used by many Internet of Things (IoT) devices to secure and encrypt data. Skipjack-encrypted data has been discovered to be vulnerable to Differential Cryptanalysis (DC) and Linear Cryptanalysis (LC) attacks. DC and LC attacks use distinguishers to predict the secret key. Distinguishers are probability tables that are used to assess an algorithm’s attack vulnerability. Much work remains to be done to prevent these two attacks and their distinguishers, particularly with regard to the Skipjack algorithm. This study employs a novel technique to protect Skipjack from DC and LC attacks. The novel method is to use the Muthavhine function on the Skipjack algorithm to convert an original
$8\times8$
F-Table to an
$8\times32$
F-Table. The Muthavhine function is a newly coined and purposefully used mathematically generated method in this study. Muthavhine function combines an enormous number of mathematical modulo operators. The vast majority of mathematical modulo operators are irreversible to attackers. The Muthavhine function perplexes the intruder by generating a new
$8\times32$
F-Table suitable for the new algorithm, which prevents intruders from performing DC and LC attacks. The Muthavhine function is able to reduce the probability of building distinguishers for DC and LC attacks from 1.09% to 0% and 4.68% to 0%, respectively.