Multi-Factor Authentication Model with Light Weight Encryption for Cloud IoT Systems
DOI:
https://doi.org/10.32628/CSEIT2511634Keywords:
Cloud-IoT Security, Multi-Factor Authentication (MFA), Lightweight Encryption, SPECK Cipher, Secure IoT CommunicationAbstract
The quick development of Cloud-IoT systems has enabled large-scale automation, universal sensing, and intelligent decision-making across various application domains, including smart cities, industrial IoT, healthcare and transportation. However, the integration of resource-constrained IoT devices with cloud platforms familiarizes significant security encounters, predominantly in authentication and in data protection. Traditional cryptographic and authentication structures look to be computationally very intensive which makes them inappropriate for low-power IoT architectures. This research recommends a robust and energy effective security framework that integrates the Multi-Factor Authentication (MFA) with the lightweight encryption to ensure secure device access, user authentication and data confidentiality in Cloud-IoT environments. The proposed MFA model incorporates possession-based, knowledge-based and behavioral factors thereby minimalizing the threat of credential compromise and the unauthorized access. Lightweight encryption algorithms such as SPECK and PRESENT are labouring to produce cryptographically secure authentication tokens and protect announcement without overloading the constrained devices. Investigational evaluations validate better-quality resistance to replay, impersonation and brute-force attacks while achieving low computational overhead. The mixture of MFA and lightweight cryptography efficiently supports trust, enhances system resilience, and provides a scalable security architecture suitable for next-generation IoT deployments.
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Beaulieu, R., Shors, D., Smith, J., Treatman-Clark, S., Weeks, B., & Wingers, L. (2015). The SIMON and SPECK lightweight block ciphers. DOI: https://doi.org/10.1145/2744769.2747946
Bogdanov, A., Knudsen, L. R., Leander, G., Paar, C., Poschmann, A., Robshaw, M. J. B., Seurin, Y., & Vikkelsoe, C. (2007). PRESENT: An ultra-lightweight block cipher. In P. Paillier & I. Verbauwhede (Eds.), Cryptographic Hardware and Embedded Systems CHES 2007, Springer. https://doi.org/10.1007/978-3-540-74735-2_31
Sicari, S., Rizzardi, A., Grieco, L. A., & Coen-Porisini, A. (2015). Security, privacy and trust in Internet of Things: The road ahead. Computer Networks, 76, 146–164. https://doi.org/10.1016/j.comnet.2014.11.008 DOI: https://doi.org/10.1016/j.comnet.2014.11.008
Roman, R., Lopez, J., & Mambo, M. (2018). Mobile edge computing, fog et al.: A survey and analysis of security threats and challenges. Future Generation Computer Systems, 78, 680–698. https://doi.org/10.1016/j.future.2016.11.009 DOI: https://doi.org/10.1016/j.future.2016.11.009
El-Hajj, M., El-Khatib, K., & Chehab, A. (2019). A survey of Internet of Things (IoT) authentication schemes. Sensors (MDPI), 19(5), 1141. https://doi.org/10.3390/s19051141 DOI: https://doi.org/10.3390/s19051141
Khan, M. A., McLaughlin, K., & Laverty, D. (2022). A survey of authentication in Internet of Things-enabled healthcare systems. IEEE Access DOI: https://doi.org/10.3390/s22239089
Fereidooni, H., Carman, M., & Eriksson, J. (2023). AuthentiSense: A scalable behavioral biometrics authentication system. NDSS Symposium 2023 DOI: https://doi.org/10.14722/ndss.2023.23194
Sahu, A. K., Sharma, S., Tripathi, S. S., & Singh, K. N. (2021). A study of authentication protocols in Internet of Things
Krašovec, A., et al. (2021). Behaviour biometrics for privacy-preserving authentication. Proceedings of the ACM Conference.
Wang, Y., Kim, S., & Lee, J. (2019). Cryptographic schemes and key management for constrained IoT devices: A review. Journal of Cryptographic Engineering / Survey.
Amin, R., Kumar, N., & Alazab, M. (2019). Secure authentication mechanisms for IoT: A survey of token-based and distributed methods. IEEE Communications Surveys.
Shrestha, R., & Lee, G. M. (2019). Secure and lightweight HMAC mutual authentication protocol for communication between IoT devices and fog nodes. Proceedings of an IEEE conference and IEEE Communications Workshops.
Yadav, A. K., Pandey, S., & Singh, R. K. (2021). Token-based lightweight authentication to secure IoT sensor nodes. International Conference Proceedings.
Rao, P. M., & Others. (2023). A comprehensive survey on authentication and secure key management in IoT. Journal of Network and Computer Applications.
Dolev, S., & Others. (2020). Lightweight cryptography for IoT applications. Sensors.
Bogdanov, A., Gueron, S., Knudsen, L., Leander, G., Paar, C., Poschmann, A., Robshaw, M., Seurin, Y., & Vikkelsoe, C. (2007). https://doi.org/10.1007/978-3-540-74735-2_31 DOI: https://doi.org/10.1007/978-3-540-74735-2_31
Sahu, A. K. (2022). Deep learning-based continuous authentication for an IoT ecosystem. Information Sciences (2022). DOI: https://doi.org/10.1016/j.compeleceng.2022.107817
Patel, R., & Singh, A. (2021). Multi-factor authentication frameworks for distributed systems and IoT. International Journal of Network Security.
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