# Securing IoT Devices against Differential-Linear (DL) Attack Used on Serpent Algorithm
###### Abstract  
Cryptographic algorithms installed on Internet of Things (IoT) devices suffer many attacks. Some of these attacks include the differential linear attack (DL). The DL attack depends on the computation of the probability of differential-linear characteristics, which yields a Differential-Linear Connectivity Table (_DLCT_). The _DLCT_ is a probability table that provides an attacker many possibilities of guessing the cryptographic keys of any algorithm such as Serpent. In essence, the attacker firstly constructs a _DLCT_ by using building blocks such as Substitution Boxes (S-Boxes) found in many algorithms' architectures. In depth, this study focuses on securing IoT devices against DL attacks used on Serpent algorithms by using three magic numbers mapped on a newly developed mathematical function called Blocker, which will be added on Serpent's infrastructure before being installed in IoT devices. The new S-Boxes with 32-bit output were generated to replace the original Serpent's S-Boxes with 4-bit output. The new S-Boxes were also inserted in Serpent's architecture. This novel approach of using magic numbers and the Blocker Function worked successfully in this study. The results demonstrated an algorithm for which its S-Box is composed of a 4-bit-output that is more vulnerable to being attacked than an algorithm in which its S-Box comprises 32-bit outputs. The novel approach of using a Blocker, developed by three magic numbers and 32-bits output S-Boxes, successfully blocked the construction of _DLCT_ and DL attacks. This approach managed to secure the Serpent algorithm installed on IoT devices against DL attacks. security of IoT devices; serpent; differential-linear attack (DL attack); differential-linear connectivity table (_DLCT_); magic numbers +
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win-win situation for both clients and suppliers [4; 5]. Even though IoT is beneficial for the community and manufacturers, there are difficulties related to the deployment of the IoT, such as privacy and security of private data. The privacy difficulties postured by the IoT are related to those postured by existing digital technologies that obtain and transmit data, especially radio-frequency identification and cloud computing. IoT devices are everywhere, and users have little experience on the know-how involved in managing data [4]. When executing an action that depends on digital technologies, including the IoT, users should consider the potential budgetary and social importance of possible digital protection occurrences concerning availability, integrity, or data confidentiality in data operation [3]. These values can weaken resources (for instance, through the interruption of transactions), threaten reputation (for example, through the disclosure of private data or website damage), or modify the business environment (for instance, through deprivation of innovation) [3; 4; 5]. Privacy encompasses the practices on which personal data can be obtained and is, consequently, one of the most prominent challenges. The processes of tracing, verification, validation of devices, all activities performed, and collecting private data from different forms can foster an environment for effortless hacking with respect to information [5]. Security is one of the common difficulties that the IoT has to address [3]. Affordability and low expense broadband connection and Wi-Fi abilities in numerous devices are required for secure localization in common areas, and transmitting them unprotected would yield them to cyber-attacks [3; 5]. IoT enables consistent data sharing between similar gadgets and distinguishes three principal components guaranteeing security--authentication, access control, and confidentiality of IoT [4]. A robust cryptographic algorithm is needed to secure data collected, used, stored, and transmitted using IoT devices [3]. IoT devices depend on cryptographic algorithms to store and transmit confidential information [6; 7; 8; 9].