Data Security in Cloud Computing: Encryption, Zero Trust, and Homomorphic Encryption
DOI:
https://doi.org/10.63282/3050-9246.IJETCSIT-V2I3P108Keywords:
Cloud computing, data security, encryption, zero trust architecture, homomorphic encryption, access control, privacy preservationAbstract
As cloud computing becomes the backbone of modern digital infrastructure, Data processing, transmission, and storage security in cloud systems has become a major worry. Because cloud systems are dynamic and multi-tenant, traditional security methods are unable to handle them, leaving them vulnerable to insider threats, data breaches as well as illegal access. The important security considerations for cloud computing are examined in this study, focusing on encryption techniques and architectural strategies to safeguard data in increasingly complex digital environments. As organizations transition to cloud-based infrastructures, protecting data confidentiality, integrity, and availability becomes a top priority, particularly in the face of dangers such insider attacks, data breaches, and illegal access. A thorough review of fundamental cloud security concepts, the functions of symmetric and asymmetric encryption, and cutting-edge the methods discussed in this article include Attribute-Based Encryption (ABE) and ABE with several authorities for more precise access control. Furthermore, it emphasizes the need for homomorphic encryption (HE) to allow secure computations on encrypted data and looks at the Zero Trust Architecture (ZTA) as a proactive security paradigm to lessen developing cyber threats
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References
[1] M. Kaur and H. Singh, “A review of cloud computing security issues,” Int. J. Grid Distrib. Comput., vol. 8, no. 5, pp. 215–222, 2015, doi: 10.14257/ijgdc.2015.8.5.21.
[2] A. Immadisetty, “Dynamic Pricing Strategies in Retail: Leveraging Real-Time Data Analytics for Competitive Advantage,” J. Recent TRENDS Comput. Sci. Eng., vol. 13, no. 1, pp. 53–65, Feb. 2025, doi: 10.70589/JRTCSE.2025.13.1.8.
[3] S. K. Sood, “A combined approach to ensure data security in cloud computing,” J. Netw. Comput. Appl., vol. 35, no. 6, pp. 1831–1838, 2012, doi: https://doi.org/10.1016/j.jnca.2012.07.007.
[4] M. E. Zhao and Y. Geng, “Homomorphic Encryption Technology for Cloud Computing,” Procedia Comput. Sci., vol. 154, pp. 73–83, 2018, doi: 10.1016/j.procs.2019.06.012.
[5] A. Immadisetty, “Dynamic Pricing Strategies in Retail: Leveraging Real-Time Data Analytics for Competitive Advantage,” J. Recent Trends Comput. Sci. Eng., vol. 13, no. 1, pp. 53–65, 2017.
[6] M. Carroll and A. Van Der Merwe, “Secure cloud computing: Benefits, risks and controls,” in 2011 Information Security for South Africa, IEEE, Aug. 2011, pp. 1–9. doi: 10.1109/ISSA.2011.6027519.
[7] P. Srivastava and R. Khan, “A Review Paper on Cloud Computing,” Int. J. Adv. Res. Comput. Sci. Softw. Eng., 2018, doi: 10.23956/ijarcsse.v8i6.711.
[8] E. Simmon, “Evaluation of cloud computing services based on NIST SP 800-145,” Gaithersburg, MD, Feb. 2018. doi: 10.6028/NIST.SP.500-322.
[9] T. Diaby and B. B. Rad, “Cloud Computing: A review of the Concepts and Deployment Models,” Int. J. Inf. Technol. Comput. Sci., vol. 9, no. 6, pp. 50–58, 2017, doi: 10.5815/ijitcs.2017.06.07.
[10] A. Gogineni, “Novel Scheduling Algorithms For Efficient Deployment Of Mapreduce Applications In Heterogeneous Computing,” Int. Res. J. Eng. Technol., vol. 4, no. 11, p. 6, 2017.
[11] F. Yahya, V. Chang, R. J. Walters, and G. B. Wills, “Security Challenges in Cloud Storages,” in 2014 IEEE 6th International Conference on Cloud Computing Technology and Science, 2014, pp. 1051–1056. doi: 10.1109/CloudCom.2014.171.
[12] A. Albugmi, M. O. Alassafi, R. Walters, and G. Wills, “Data security in cloud computing,” 5th Int. Conf. Futur. Gener. Commun. Technol. FGCT 2016, no. October 2017, pp. 55–59, 2016, doi: 10.1109/FGCT.2016.7605062.
[13] W. R. Claycomb and A. Nicoll, “Insider Threats to Cloud Computing: Directions for New Research Challenges,” in 2012 IEEE 36th Annual Computer Software and Applications Conference, 2012, pp. 387–394. doi: 10.1109/COMPSAC.2012.113.
[14] S. Balasubramaniam and V. Kavitha, “A survey on data encryption tecniques in cloud computing,” Asian J. Inf. Technol., vol. 13, no. 9, pp. 494–505, 2014, doi: 10.3923/ajit.2014.494.505.
[15] R. Cahya, P. Arief, A. Novriza, and A. Kohei, “Noble Method for Data Hiding using Steganography Discrete Wavelet Transformation and Cryptography Triple Data Encryption Standard: DES,” Int. J. Adv. Comput. Sci. Appl., vol. 9, no. 11, pp. 261–266, 2018, doi: 10.14569/IJACSA.2018.091136.
[16] S. Kamara and K. Lauter, “Cryptographic Cloud Storage,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6054 LNCS, 2010, pp. 136–149. doi: 10.1007/978-3-642-14992-4_13.
[17] P. K. Premkamal, P. S. Kumar, and A. Pja, “Attribute based encryption in cloud computing: A survey, gap analysis, and future directions,” J. Netw. Comput. Appl., vol. 108, pp. 37–52, Apr. 2018, doi: 10.1016/j.jnca.2018.02.009.
[18] P. Sun, “Privacy Protection and Data Security in Cloud Computing: A Survey, Challenges, and Solutions,” IEEE Access, vol. 7, pp. 147420–147452, 2019, doi: 10.1109/ACCESS.2019.2946185.
[19] V. Biksham and D. Vasumathi, “Homomorphic Encryption Techniques for securing Data in Cloud Computing: A Survey,” Int. J. Comput. Appl., vol. 160, no. 6, pp. 1–5, 2017, doi: 10.5120/ijca2017913063.
[20] [20] M. Ogburn, C. Turner, and P. Dahal, “Homomorphic encryption,” Procedia Comput. Sci., vol. 20, pp. 502–509, 2013, doi: 10.1016/j.procs.2013.09.310.
[21] A. Acar, H. Aksu, A. S. Uluagac, and M. Conti, “A survey on homomorphic encryption schemes: Theory and implementation,” ACM Comput. Surv., vol. 51, no. 4, 2018, doi: 10.1145/3214303.
[22] C. Decusatis, P. Liengtiraphan, A. Sager, and M. Pinelli, “Implementing Zero Trust Cloud Networks with Transport Access Control and First Packet Authentication,” Proc. - 2016 IEEE Int. Conf. Smart Cloud, SmartCloud 2016, pp. 5–10, 2016, doi: 10.1109/SmartCloud.2016.22.
[23] K. Delbene, M. Medin, and R. Murray, “The Road to Zero Trust (Security),” pp. 1–10, 2019.
[24] L. B. Bhajantri and T. Mujawar, “A Survey of Cloud Computing Security Challenges, Issues and their Countermeasures,” in Proceedings of the 3rd International Conference on I-SMAC IoT in Social, Mobile, Analytics and Cloud, I-SMAC 2019, 2019. doi: 10.1109/I-SMAC47947.2019.9032545.
[25] K. P. Singh, V. Rishiwal, and P. Kumar, “Classification of Data to Enhance Data Security in Cloud Computing,” in 2018 3rd International Conference On Internet of Things: Smart Innovation and Usages (IoT-SIU), 2018, pp. 1–5. doi: 10.1109/IoT-SIU.2018.8519934.
[26] Z. H. Mahmood and M. K. Ibrahem, “New Fully Homomorphic Encryption Scheme Based on Multistage Partial Homomorphic Encryption Applied in Cloud Computing,” in 2018 1st Annual International Conference on Information and Sciences (AiCIS), 2018, pp. 182–186. doi: 10.1109/AiCIS.2018.00043.
[27] Z. Diao, Q. Wang, N. Su, and Y. Zhang, “Study on Data Security Policy Based on Cloud Storage,” in Proceedings - 3rd IEEE International Conference on Big Data Security on Cloud, BigDataSecurity 2017, 3rd IEEE International Conference on High Performance and Smart Computing, HPSC 2017 and 2nd IEEE International Conference on Intelligent Data and Security, IDS 2017, 2017. doi: 10.1109/BigDataSecurity.2017.12.
[28] A. Albugmi, M. O. Alassafi, R. Walters, and G. Wills, “Data security in cloud computing,” in 2016 Fifth International Conference on Future Generation Communication Technologies (FGCT), 2016, pp. 55–59. doi: 10.1109/FGCT.2016.7605062.
[29] Chinta, P. C. R., & Karaka, L. M. (2020). Agentic AI and Reinforcement Learning: Towards More Autonomous and Adaptive AI Systems.
[30] Kalla, D., Kuraku, D. S., & Samaah, F. (2021). Enhancing cyber security by predicting malwares using supervised machine learning models. International Journal of Computing and Artificial Intelligence, 2(2), 55-62.
[31] Katari, A., & Kalla, D. (2021). Cost Optimization in Cloud-Based Financial Data Lakes: Techniques and Case Studies. ESP Journal of Engineering & Technology Advancements (ESP-JETA), 1(1), 150-157.
[32] Kalla, D., Smith, N., Samaah, F., & Polimetla, K. (2021). Facial Emotion and Sentiment Detection Using Convolutional Neural Network. Indian Journal of Artificial Intelligence Research (INDJAIR), 1(1), 1-13.
[33] Routhu, K., Bodepudi, V., Jha, K. M., & Chinta, P. C. R. (2020). A Deep Learning Architectures for Enhancing Cyber Security Protocols in Big Data Integrated ERP Systems. Available at SSRN 5102662.
[34] Kuraku, S., & Kalla, D. (2020). Emotet malware a banking credentials stealer. Iosr J. Comput. Eng, 22, 31-41.
[35] Kalla, D., & Samiuddin, V. (2020). Chatbot for medical treatment using NLTK Lib. IOSR J. Comput. Eng, 22, 12.
[36] Routhu, K., & Jha, K. M. (2021). Leveraging Big Data Analytics and Machine Learning Techniques for Sentiment Analysis of Amazon Product Reviews in Business Insights. Available at SSRN 5106490.
[37] Chinta, P. C. R., & Katnapally, N. (2021). Neural Network-Based Risk Assessment for Cybersecurity in Big Data-Oriented ERP Infrastructures. Neural Network-Based Risk Assessment for Cybersecurity in Big Data-Oriented ERP Infrastructures.
[38] Karaka, L. M. (2021). Optimising Product Enhancements Strategic Approaches to Managing Complexity. Available at SSRN 5147875.
[39] Boppana, S. B., Moore, C. S., Bodepudi, V., Jha, K. M., Maka, S. R., & Sadaram, G. AI And ML Applications In Big Data Analytics: Transforming ERP Security Models For Modern Enterprises.
