Design and Security Analysis of a Dynamic Key-Based Lightweight Encryption Algorithm for Resource-Constrained Embedded Systems
Keywords:
Dynamic key encryption, Embedded systems, IoT security, Lightweight cryptography, XOR encryptionAbstract
This paper focuses on improving security in resource-constrained embedded systems and Internet of Things (IoT) networks by developing an efficient, lightweight encryption technique with low computational requirements. The proposed approach introduces a dynamic key-based encryption algorithm that combines XOR operations with an iterative key evolution process and a feedback mechanism to strengthen data security. The methodology involves implementing the encryption algorithm in the C programming language and evaluating its performance through statistical analysis using Python tools. Security assessment is carried out using various parameters such as entropy, histogram distribution, correlation coefficient, and avalanche effect to measure the effectiveness of the encryption process. The results demonstrate increased randomness in encrypted data and reduced correlation between plaintext and ciphertext, indicating stronger security characteristics. The main contribution of the work lies in integrating dynamic key evolution with lightweight encryption methods to provide improved protection while maintaining computational efficiency for embedded and IoT applications.
References
P. Panahi, C. Bayılmış, U. Çavuşoğlu and S. Kaçar, “Performance evaluation of lightweight encryption algorithms for IoT-based applications,” Arabian Journal for Science and Engineering, vol. 46, pp. 4015–4037, Feb. 2021.
I. K. Dutta, B. Ghosh and M. Bayoumi, “Lightweight cryptography for Internet of Insecure Things: A survey,” 2019 IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), Las Vegas, NV, USA, 2019, pp. 475–481.
C. Silva, N. Tenório, and J. Bernardino, “Lightweight encryption algorithms for IoT,” Computers, vol. 14, no. 12, Nov. 2025.
S. B. Prasad and P. Madhumathy, “Long term evolution for secured smart railway communications using Internet of Things,” in Machine Learning Algorithms for Industrial Applications, S. K. Das, S. P. Das, N. Dey, and A.-E. Hassanien, Eds., Springer Nature, 2021, pp. 285–300.
S. Sivasankar, D. Devasenapathy, P Madhumathy, G. Kaur, Y. Sharma, and P. Rana, “Design and modeling of graph theory approach based routing algorithm,” International Journal on Interactive Design and Manufacturing (IJIDeM), vol. 18, pp. 6013–6021, Aug. 2023.
A. Shafique, A. Mehmood, M. Alawida, A. N. Khan, and J. Shuja, “Lightweight image encryption scheme for IoT environment and machine learning-driven robust S-box selection,” Telecommunication Systems, vol. 88, Jan. 2025.
I. Banerjee and P. Madhumathy, “IoT based agricultural business model for estimating crop health management to reduce farmer distress using SVM and machine learning,” in Internet of Things and Analytics for Agriculture, Volume 3, P. K. Pattnaik, R. Kumar, and S. Pal, Eds., Springer International Publishing, 2022, pp. 165–183.
National Institute of Standards and Technology (NIST), Lightweight Cryptography Standardization Process: Final Report. Gaithersburg, MD, USA: National Institute of Standards and Technology, 2023.
P. Madhumathy and S. Dhandapani, “Modelling and simulation of a novel relay node based secure routing protocol using multiple mobile sink for Wireless Sensor Networks,” The Scientific World Journal, vol. 2015, no. 1, Oct. 2015.
M. Usman, I. Ahmed, M. I. Aslam, S. Khan and U. A. Shah, “SIT: A lightweight encryption algorithm for secure Internet of Things,” International Journal of Advanced Computer Science and Applications, vol. 8, no. 1, pp. 402–411, 2017.
K. Munjal and R. Bhatia, “A systematic review of homomorphic encryption and its contributions in healthcare industry,” Complex & Intelligent Systems, vol. 9, pp.3759–3786, May 2022.
C. Manifavas, G. Hatzivasilis, K. Fysarakis, and K. Rantos, “Lightweight cryptography for embedded systems – a comparative analysis,” in Data Privacy Management and Autonomous Spontaneous Security, Springer , Jan. 2014, pp. 333–349.
R. M. A. Al-Azzawi and S. S. M. Al-Dabbagh, “A lightweight encryption algorithm to secure IoT devices,” International Journal of Applied Sciences and Technology, vol. 5, no. 3, pp. 37–62, 2023.
B. K. Sedraoui, A. Benmachiche, and A. Makhlouf, “Developing and evaluating lightweight cryptographic algorithms for secure embedded systems in IoT devices,” arXiv, Jan. 2026.
N. V. Hegde, S. Bare, K. B, Ramesh and A. Ibrahim, “eFPE: Design, implementation, and evaluation of a lightweight format-preserving encryption algorithm for embedded systems,” arXiv, Nov. 2025.
P. Madhumathy, D. Sivakumar, “Mobile sink based reliable and energy efficient data gathering technique for WSN,” Journal of Theoretical and Applied Information Technology, vol. 61, no. 1, Mar. 2014.
W. J. Buchanan and L. Maglaras, “Review of the NIST light-weight cryptography finalists,” 2023 19th International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT), Pafos, Cyprus, 2023, pp. 469–474.
M. R. Suma and P. Madhumathy, “Acquisition and mining of agricultural data using ubiquitous sensors with Internet of Things,” International Conference on Computer Networks and Communication Technologies, Sep. 2018, pp. 249–261.
