Securing Beyond-5G Communications in Cloud Assisted IoT Ecosystems via Lightweight Encryption Techniques
| International Journal of Electronics and Communication Engineering |
| © 2026 by SSRG - IJECE Journal |
| Volume 13 Issue 3 |
| Year of Publication : 2026 |
| Authors : S. Almelu, Prabhakar K, Sunitha T, Durga Devi A |
How to Cite?
S. Almelu, Prabhakar K, Sunitha T, Durga Devi A, "Securing Beyond-5G Communications in Cloud Assisted IoT Ecosystems via Lightweight Encryption Techniques," SSRG International Journal of Electronics and Communication Engineering, vol. 13, no. 3, pp. 301-311, 2026. Crossref, https://doi.org/10.14445/23488549/IJECE-V13I3P124
Abstract:
Faster speeds of Beyond-5G (B5G) communication technologies have allowed connectivity in Internet of Things (IoT) ecosystems on an unprecedented scale, although this progression has also increased existing security vulnerabilities by making most IoT devices resource-constrained. The main issue is to balance strong security with the low computing, memory, and power capabilities of IoT endpoints that cannot be effectively supported by conventional encryption algorithms such as RSA or AES. To deal with this, the suggested approach, Lightweight Encryption in Beyond-5G IoT Security (LEBIS), proposes specialized cryptographic algorithms that are optimized in low-resource settings, focusing on small code size, power usage, and resistance to side-channel and quantum attacks. LEBIS incorporates post-quantum cryptographic algorithms like lattice-based and hash based schemes with lightweight key management protocols, which guarantee the safety of communication without damaging the working of the devices. The results of the experiment have proven that LEBIS can establish a high level of data confidentiality and integrity, and in the process, the data encryption is enhanced, and real-time Internet of Things can be supported by up to 80% higher efficiency at practical throughputs. It concludes with the statement that LEBIS is capable of ensuring B5G-enabled Cloud Assisted IoT Ecosystems because it can converge lightweight cryptographic rigor with the harsh resource limitations of the IoT devices, and hence is a promising approach to ensure security in IoT systems in future smart pervasive environments. It is therefore a work that adds a scalable and adaptable method that is vital in the progression of trust to next-generation IoT networks.
Keywords:
Beyond-5G, Internet of Things, lightweight encryption, post-quantum cryptography, resource-constrained devices, IoT security.
References:
[1] Pejman Panahi et al., “Performance Evaluation of Lightweight Encryption Algorithms for IoT-based Applications,” Arabian Journal for Science and Engineering, vol. 46, pp. 4015-4037, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Ujjania NC, Manish Pradhan, and Ujjania VK, “Growth and Condition of Indian Major Carps (Catla Catla, Labeo Rohita and Cirrhinus Mrigala) Cultured in Earthen Ponds with Saline Water,” Discovery Agriculture, vol. 12, no. 25, pp. 1-8, 2026.
[Publisher Link]
[3] Jihane Jebranea, and Saiida Lazaara, “A Performance Comparison of Lightweight Cryptographic Algorithms Suitable for IoT Transmissions,” General Letters in Mathematics, vol. 10, no. 2, pp. 46-53, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[4] Abdullah Sevin, and Abdu Ahmed Osman Mohammed, “A Survey on Software Implementation of Lightweight Block Ciphers for IoT Devices,” Journal of Ambient Intelligence and Humanized Computing, vol. 14, pp. 1801-1815, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Mohammed El-hajj, Hussien Mousawi, and Ahmad Fadlallah, “Analysis of Lightweight Cryptographic Algorithms on IoT Hardware Platform,” Future Internet, vol. 15, no. 2, pp. 1-29, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[6] M. Arun et al., “Internet of Things and Deep Learning-Enhanced Monitoring for Energy Efficiency in Older Buildings,” Case Studies in Thermal Engineering, vol. 61, pp. 1-18, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Mahendra Shridhar Naik, Desai Karanam Sreekantha, and Kanduri V.S.S.S.S. Sairam “Comparative Study of Block Ciphers Implementation for Resource-Constrained Devices,” Radioelectronics and Communications Systems, vol. 66, pp. 123-137, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[8] M. Arun, and Gokul Gopan, “Effects of Natural Light on Improving the Lighting and Energy Efficiency of Buildings: Toward Low Energy Consumption and CO2 Emission,” International Journal of Low-Carbon Technologies, vol. 20, pp. 1047-1056, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Vinita Bhandiwad, and Lakshmappa K. Ragha, “Enhancing the Security of IOT Enabled Systems using Light Weight Hybrid Cryptography Models,” Cluster Computing, vol. 28, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Salman Ali, and Faisal Anwer, “Secure IoT Framework for Authentication and Confidentiality Using Hybrid Cryptographic Schemes,” International Journal of Information Technology, vol. 16, pp. 2053-2067, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Muhammad Nauman Khan, Asha Rao, and Seyit Camtepe, “Lightweight Cryptographic Protocols for IoT-Constrained Devices: A Survey,” IEEE Internet of Things Journal, vol. 8, no. 6, pp. 4132-4156, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Salman Ali, and Faisal Anwer, “An IoT-Enabled Cloud Computing Model for Authentication and Data Confidentiality using Lightweight Cryptography,” Arabian Journal for Science and Engineering, vol. 50, pp. 15907-15929, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Pericle Perazzo et al., “Performance Evaluation of Attribute-Based Encryption on Constrained IoT Devices,” Computer Communications, vol. 170, pp. 151-163, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Shruti et al., “Attribute-Based Encryption Schemes for Next Generation Wireless IoT Networks: A Comprehensive Survey,” Sensors, vol. 23, no. 13, pp. 1-33, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Ana Goulart et al., “On wide-Area IoT Networks, Lightweight Security and Their Applications—A Practical Review,” Electronics, vol. 11, no. 11, pp. 1-40, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Antonio Francesco Gentile et al., “A Performance Analysis of Security Protocols for Distributed Measurement Systems based on Internet of Things with Constrained Hardware and Open Source Infrastructures,” Sensors, vol. 24, no. 9, pp. 1-22, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Kurunandan Jain et al., “A Lightweight Multi-Chaos-Based Image Encryption Scheme for IoT Networks,” IEEE Access, vol. 12, pp. 62118-62148, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Belal Sudqi Khater et al., “Classifier Performance Evaluation for Lightweight IDS using Fog Computing in IoT Security,” Electronics, vol. 10, no. 14, pp. 1-52, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[19] P. William et al., “Crime Analysis Using Computer Vision Approach with Machine Learning,” Mobile Radio Communications and 5G Networks, vol. 588, pp. 297-315, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Muhammad Rana, Quazi Mamun, and Rafiqul Islam, “Balancing Security and Efficiency: A Power Consumption Analysis of a Lightweight Block Cipher,” Electronics, vol. 13, no. 21, pp. 1-35, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Rabie A. Ramadan et al., “LBC-IoT: Lightweight Block Cipher for IoT Constraint Devices,” Computers, Materials & Continua, vol. 67, no. 3, pp. 3563-3579, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Sohel Rana et al., “RBFK Cipher: A Randomized Butterfly Architecture-Based Lightweight Block Cipher for IoT Devices in the Edge Computing Environment,” Cybersecurity, vol. 6, pp. 1-19, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Kranthi Kumar Singamaneni, “A Novel Lightweight Hybrid Cryptographic Framework for Secure Smart Card Operations,” EURASIP Journal on Information Security, vol. 2025, pp. 1-21, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Haotian Yin et al., “LSNCP: Lightweight and Secure Numeric Comparison Protocol for Wireless Body Area Networks,” IEEE Internet of Things Journal, vol. 10, no. 5, pp. 13247-13263, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Omar Abdullah Saleh, and Mesut Cevik, “Secure Edge-Based Smart Grid Communication using Lightweight Authentication Modeling with Autoencoders and Real-World Data,” Discover Computing, vol. 28, pp. 1-24, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Secure Access Control IoT Edge Dataset, Kaggle. [Online]. Available: https://www.kaggle.com/datasets/zoya77/secure access-control-iot-edge-dataset
[27] Aman Kumar et al., “Hybrid Cryptographic Approach for Strengthening IoT and 5G/B5G Network Security,” Scientific Reports, vol. 15, pp. 1-20, 2025.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Bongani Mthethwa, and Austin Smith, “Analyzing Next-Generation Encryption Protocols for Drone-Generated Traffic Data in 5G-Driven Smart Grids,” Northern Reviews on Smart Cities, Sustainable Engineering, and Emerging Technologies, vol. 9, no. 11, pp. 1-13, 2024.
[Google Scholar] [Publisher Link]
[29] Rasha Hussein Joudah, and Mehdi Ebady Manaa, “Enhancing Secure 5G-AKA Protocol Using ASCON Lightweight Cryptography,” Journal of Advanced Research Design, vol. 139, no. 1, pp. 201-217, 2026.
[CrossRef] [Google Scholar] [Publisher Link]

10.14445/23488549/IJECE-V13I3P124