# Software Design and Experimental Evaluation of a Reduced AES for IoT Applications
## 2 Related Work
### NIST Tests for Cryptographic Algorithms  
NIST recommends several techniques to verify the randomness of binary sequences generated from cryptographic algorithms and pseudorandom number generators. In April 2010, the NIST test suite was first presented in a special publication (800-22 rev1a) [10]. NIST tests are used for hypothesis testing and are usually conducted to determine if a data sample shows that a certain condition is true for an entire population. The tests are designed to evaluate data sequences for a specific null hypothesis. If the outcome of the test satisfies the null hypothesis, it is concluded that the data sequence is random. Conversely, if the outcome of the test satisfies the alternative hypothesis, then it is concluded that the data sequence is not random. Each test examines the data sequence based on the null hypothesis, to determine whether the cryptographic algorithm is producing random values.  
The NIST test suite [10; 27] has been used to assess the randomness of several cryptographic algorithms [28; 29; 30; 31]. The competition process for selecting the AES involves a rigorous series of randomness evaluations. The experiment was fixed to 0.01 significance. The author in [28] evaluated several cryptographic algorithms, including Rjindael, Serpent, Twofish, RC6, and Mars, highlighting the fact that the randomness of the ciphertext is correlated with a specific number of rounds for each cryptographic algorithm. For example, Rjindael passed the randomness tests after the 3 rd round, Serpent and RC6 after the 4 th, and Mars after the 6 th.  
The authors in [29] presented a framework based on the NIST suite to evaluate the randomness outcomes of cryptographic algorithms. The proposed framework used three NIST statistical tests to evaluate the randomness of block ciphers and stream ciphers, including TEA, Camellia, and LEX. The results of statistical tests indicated the percentage of successes from different generated sequence lengths. The authors concluded that the  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Study** & **Context IoT Application** & **Security Objective** & **Improvement Concer for IoT** \\ \hline \multirow{4}{*}{[20; 26]} & \multirow{4}{*}{IoT eHealth} & Privacy-preserving eHealth system to achieve patient privacy and address IoT environment requirements more effectively using Identity-Based Cryptography & \multirow{4}{*}{Low communication computation, memory, and energy consumption energy consumption} \\ \cline{3-4}  & & & \\ \hline \multirow{4}{*}{[20; 21]} & Internet of Medical Things (IoMT) & Improve an intrusion detection approach for the IoMT & \multirow{4}{*}{Low communication computation, memory, and energy consumption} \\ \cline{3-4}  & & & \\ \cline{1-1} \cline{3-4}  & & & \\ \cline{1-1} \cline{3-4}  & & & \\ \cline{1-1} \cline{3-4}  & & & \\ \hline \multirow{4}{*}{[21; 23]} & Surveillance for IoT healthcare application & Intelligent integration of chaotic encryption to secure the healthcare application & \multirow{4}{*}{Competitive and real-time encryption throughput} \\ \cline{1-1} \cline{3-4}  & & & \\ \cline{1-1} \cline{3-4}  & & & \\ \cline{1-1} \cline{3-4}  & & & \\ \hline \multirow{4}{*}{[23; 24]} & \multirow{4}{*}{Application of augmented reality (AR) within a smart city} & System security guaranteed through deployment of lightweight encryption used with low-powered IoT devices & Fine-grained access control without a lengthy user authorization process \\ \cline{1-1} \cline{3-4}  & & & \\ \hline \hline \end{tabular}
\end{table}
Table 1: Comparison between lightweight approaches.  
selected cryptographic algorithms showed a reliable degree of randomness based on the selected NIST tests.