Integration of Biometric Encryption Technology Combining Biometric Authentication with Cryptographic Algorithms to Enhance Cloud Network Security

References

[1] Arulananth, T., Baskar, M., Anbarasu, V., Thiagarajan, R., Rajendran, T., & Balaji, A. (2021). Multi party secure data access management in cloud using user centric block chain data encryption. Pattern Recognition Letters, 152, 295-301. https://doi.org/10.1016/j.patrec.2021.10.029

[2] Babu, P. (2023). Cloud data security enhancements through the biometric and encryption system [Unpublished master's thesis]. School of Computing, National College of Ireland.

[3] Bagga, P., Mitra, A., Das, A., Vijayakumar, P., Park, Y., & Karuppiah, M. (2022). Secure biometric-based access control scheme for future IoT-enabled cloud-assisted video surveillance system. Computer Communications, 195, 27-39. https://doi.org/10.1016/j.comcom.2022.08.003

[4] Bedari, A., Wang, S., & Yang, W. (2022). A secure online fingerprint authentication system for industrial IoT devices over 5G networks. Sensors, 22(19), Article 7609. https://doi.org/10.3390/s22197609

[5] Cachet, C., Ahmad, S., Demarest, L., Riback, S., Hamlin, A., & Fuller, B. (2022). Multi random projection inner product encryption, applications to proximity searchable encryption for the iris biometric. In Proceedings of the 2022 ACM Asia Conference on Computer and Communications Security (AsiaCCS '22) (pp. 1-15). ACM. https://doi.org/10.1145/3488932.3497754

[6] Elreesh, J., & Abu-Naser, S. (2019). Cloud network security based on biometrics cryptography intelligent tutoring system. International Journal of Academic Information Systems Research (IJAISR), 3(3), 37-70.

[7] El-Sofany, H., Bouallegue, B., & El-Latif, A. A. A. (2024). A proposed biometric authentication hybrid approach using iris recognition for improving cloud security. Heliyon, 10(6), Article e36390. https://doi.org/10.1016/j.heliyon.2024.e36390

[8] Gumaei, A., Sammouda, R., Al-Salman, A., & Alsand, A. (2019). Anti-spoofing cloud-based multi-spectral biometric identification system for enterprise security and privacy-preservation. Journal of Parallel and Distributed Computing, 124, 27-40. https://doi.org/10.1016/j.jpdc.2018.10.005

[9] Gupta, B., Gaurav, A., & Arya, V. (2024). Fuzzy logic and biometric-based lightweight cryptographic authentication for metaverse security. Applied Soft Computing, 164, Article 111973. https://doi.org/10.1016/j.asoc.2024.111973

[10] Hamsanandhini, S., & Balasubramanie, P. (2024). IoT data encryption and phrase search-based efficient processing using a fully homomorphic-based SE (FHSE) scheme. Pervasive and Mobile Computing, 103, Article 101952. https://doi.org/10.1016/j.pmcj.2024.101952

[11] Helmy, M., El-Rabaie, E., El-Dokany, I., & El-Samie, F. E. (2023). A novel cancellable biometric recognition system based on Rubik's cube technique for cyber-security applications. Optik, 285, Article 170475. https://doi.org/10.1016/j.ijleo.2022.170475

[12] Jeyakumar, M., & Samraj, J. (2024). Secure medical sensor monitoring framework using novel hybrid encryption algorithm driven by internet of things. Measurement: Sensors, 33, Article 101122. https://doi.org/10.1016/j.measen.2024.101122

[13] Kumar, V., Venkatachalam, K., Prabu, P., Almutairi, A., & Abouhawwash, M. (2021). Secure biometric authentication with de-duplication on distributed cloud storage. PeerJ Computer Science, 7, Article e569. https://doi.org/10.7717/peerj-cs.569

[14] Lu, Y., & Zhao, D. (2023). Providing impersonation resistance for biometric-based authentication scheme in mobile cloud computing service. Computer Communications, 182, 22-30. https://doi.org/10.1016/j.comcom.2021.10.029

[15] Mostafa, A., Ezz, M., Elbashir, M., Alruily, M., Hamouda, E., Alsarhani, M., & Said, W. (2023). Strengthening cloud security: An innovative multi-factor multi-layer authentication framework for cloud user authentication. Applied Sciences, 13(19), Article 10871. https://doi.org/10.3390/app131910871

[16] Otta, S., Panda, S., Gupta, M., & Hota, C. (2023). A systematic survey of multi-factor authentication for cloud infrastructure. Future Internet, 15(4), Article 146. https://doi.org/10.3390/fi15040146

[17] Praakash, G., Khanna, P., Kumar, S., & Pragya. (2023). A biometric-based encryption method for secure data sharing in cloud environment. In Proceedings of the International Symposium on Securing Next-Generation Systems using Future Artificial Intelligence Technologies (SNSFAIT 2023). CEUR Workshop Proceedings.

[18] Rahman, K., Hridoy, M., Rahman, M., Islam, R., & Banik, S. (2024). Highly secured and effective management of app-based online voting system using RSA encryption and decryption. Heliyon, 10(4), Article e25373. https://doi.org/10.1016/j.heliyon.2024.e25373

[19] Ramalingam, V., Saminathan, R., & Baalamurugan, K. (2023). Fork-hook encryption policy based secured data centric routing gateway for proactive trust ware data transmission in WBSN. Measurement: Sensors, 27, Article 100760. https://doi.org/10.1016/j.measen.2023.100760

[20] Shruti, Rani, S., & Srivastava, G. (2024). Secure hierarchical fog computing-based architecture for industry 5.0 using an attribute-based encryption scheme. Expert Systems with Applications, 235, Article 121180. https://doi.org/10.1016/j.eswa.2023.121180

[21] Umar, T., Nadeem, M., & Anwer, F. (2024). Chaos based image encryption scheme to secure sensitive multimedia content in cloud storage. Expert Systems with Applications, 257, Article 125050. https://doi.org/10.1016/j.eswa.2024.125050

[22] Unal, D., Al-Ali, A., Catak, F., & Hammoudeh, M. (2021). A secure and efficient Internet of Things cloud encryption scheme with forensics investigation compatibility based on identity-based encryption. Future Generation Computer Systems, 125, 433-445. https://doi.org/10.1016/j.future.2021.06.050

[23] Wu, D., Li, L., Tian, W., Xian, H., & Tian, C. (2024). Biometric identification on the cloud: A more secure and faster construction. Information Sciences, 669, Article 120553. https://doi.org/10.1016/j.ins.2024.120553

[24] Zafir, E., Akter, A., Islam, A., Hasib, M., Islam, T., Sarker, S., & Muyeen, S. (2024). Enhancing security of Internet of Robotic Things: A review of recent trends, practices, and recommendations with encryption and blockchain techniques. Internet of Things, 28, Article 101357. https://doi.org/10.1016/j.iot.2024.101357

[25] Zhao, M., & Geng, Y. (2019). Homomorphic encryption technology for cloud computing. In Proceedings of the 8th International Congress of Information and Communication Technology (ICICT 2019). https://doi.org/10.1016/j.procs.2019.06.012

[26] Zhou, Y., Zhao, L., Jin, Y., & Li, F. (2022). Backdoor-resistant identity-based proxy re-encryption for cloud-assisted wireless body area networks. Information Sciences, 604, 80-96. https://doi.org/10.1016/j.ins.2022.05.007

@article{1711617,
      author = {Asogwa, T. C., Omeje, K. N.},
      title = {Integration of Biometric Encryption Technology Combining Biometric Authentication with Cryptographic Algorithms to Enhance Cloud Network Security},
      journal = {Iconic Research And Engineering Journals},
      year = {2025},
      volume = {9},
      number = {4},
      pages = {1869-1879},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1711617.pdf},
      abstract = {The growing rate of using cloud computing has posed a serious dilemma in providing the security, privacy, and the integrity of authentication of data. Older protection systems, including passwords and two-factor authentication, frequently prove susceptible to cyberattack and identities theft. This paper discusses how to use the biometric encryption technology (i.e. biometric authentication (e.g., facial recognition, fingerprints) + cryptographic algorithm) to secure the cloud network. The analysis of the recent literature (20192024) demonstrates that some of the encryption methods, such as RSA, AES, ECC, and homomorphic encryption, and even the combination of blockchain, IoT, and deep learning are effective. Biometric encryption schemes, including key-binding, key-generation, fuzzy vault, biometric hashing, and cancellable biometrics are also discussed and their application to the protection of sensitive data on the cloud is highlighted. Nevertheless, there has been significant progress, and there are still difficulties in the domain of data privacy, computational cost, scalability, and regulatory compliance. In order to overcome these constraints, future studies ought to emphasise on the creation of lightweight, and privacy preserving biometric encryption models, with capability of operating in real time, in a cloud environment. The results highlight the fact that biometric encryption is a progressive strategy of attaining robust, dynamic and user-friendly cloud data security in the emerging digital ecosystem.},
      keywords = {Biometric Encryption; Cloud Computing Security; Cryptography; Deep Learning; Data Privacy},
      month = {October},
  }