Designing High-Performance Distributed Systems for In-Memory Secure Data Processing in Cloud Security Analytics
Keywords:
Distributed Systems, In-Memory Computing, Cloud Security Analytics, Secure Data Processing, High-Performance Computing, Real-Time Threat DetectionAbstract
The surge of cloud-based apps and advanced cyber threats has led to a huge demand for high-powered security analytics that can ingest and process enormous amounts of data in real time. Conventional disk-based centralized security analysis systems tend to have high latency, limited scalability and insufficient privacy of sensitive data. To cope with these issues, we introduce in this paper the design of a high-performance distributed in-memory secure data processing system for cloud security analytics. The proposed model employs distributed in-memory computing, parallel processing and secure data management techniques to support us with low-latency threat analysis and real-time analytics. Advanced security features, such as data encryption in memory, secure access management, and isolation across distributed nodes are included to maintain the confidentiality and integrity of data during analytics processing. The system is deployable in a scalable form factor across cloud platforms, and yet also achieves fault tolerance and resource efficiency. Experimental results show large savings in terms of processing, types response and scalability of traditional disk-centric security analytics platforms. The results show in-memory distributed processing can provide a viable platform for next-generation cloud security analytics, leading to faster threat identification, increased operation efficiency, and strengthened data protection in the ever-evolving cloudy world.
Downloads
References
. Abbas, M.S.; Mahdi, S.S.; Hussien, S.A. Security improvement of cloud data using hybrid cryptography and steganography. In Proceedings of the 2020 international conference on computer science and software engineering (CSASE), Duhok, Iraq, 16–18 February 2020; pp. 123–127.
. Velmurugadass, P.; Dhanasekaran, S.; Anand, S.S.; Vasudevan, V. Enhancing Blockchain security in cloud computing with IoT environment using ECIES and cryptography hash algorithm. Mater. Today Proc. 2021, 37, 2653–2659. [CrossRef]
Thabit, F.; Alhomdy, S.; Al-Ahdal, A.H.; Jagtap, S. A new lightweight cryptographic algorithm for enhancing data security in cloud computing. Glob. Transitions Proc. 2021, 2, 91–99. [CrossRef]
. Mohammed, S.; Nanthini, S.; Krishna, N.B.; Srinivas, I.V.; Rajagopal, M.; Kumar, M.A. A new lightweight data security system for data security in the cloud computing. Meas. Sens. 2023, 29, 100856. [CrossRef] [5]. Chen, Y.; Tang, C.; Yi, Z. A novel image encryption scheme based on PWLCM and standard map. Complexity 2020, 2020, 3026972. [CrossRef]
. Mirzajani, S.; Moafimadani, S.S.; Roohi, M. A New Encryption Algorithm Utilizing DNA Subsequence Operations for Color Images. AppliedMath 2024, 4, 1382–1403. [CrossRef]
. Lin, H.; Deng, X.; Yu, F.; Sun, Y. Diversified butterfly attractors of memristive HNN with two memristive systems and application in IoMT for privacy protection. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 2024, 44, 304–316. [CrossRef]
. Ding, S.; Lin, H.; Deng, X.; Yao, W.; Jin, J. A hidden multiwing memristive neural network and its application in remote sensing data security. Expert Syst. Appl. 2025, 277, 127168. [CrossRef]
. Xing, B.; Wang, D.; Yang, Y.; Wei, Z.; Wu, J.; He, C. Accelerating DES and AES algorithms for a heterogeneous many-core processor. Int. J. Parallel Program. 2021, 49, 463–486. [CrossRef]
. Baladhay, J.S.; Gamido, H.V.; Edjie, M. Large file encryption in a Reduced-Round Permutation-Based AES file management system. Indones. J. Electr. Eng. Comput. Sci. 2024, 34, 2021–2031. [CrossRef]
. Kilber, N.; Kaestle, D.; Wagner, S. Cybersecurity for quantum computing. arXiv 2021, arXiv:2110.14701.
. Sarah, D.; Peter, C. On the practical cost of Grover for AES key recovery. In Proceedings of the Presentation at the 5th NIST PQC Standardization Conference, Rockville, MD, USA, 10–12 April 2024.
. Grassl, M.; Langenberg, B.; Roetteler, M.; Steinwandt, R. Applying Grover’s algorithm to AES: Quantum resource estimates. In Proceedings of the International Workshop on Post-Quantum Cryptography, Fukuoka, Japan, 24–26 February 2016; pp. 29–43.
. Open Quantum Safe. Available online: https://openquantumsafe.org/ (accessed on 6 July 2025).
. Ahmed, M.; Byreddy, S.; Nutakki, A.; Sikos, L.F.; Haskell-Dowland, P. ECU-IoHT: A dataset for analyzing cyberattacks in Internet of Health Things. Ad Hoc Netw. 2021, 122, 102621. [CrossRef]
. Yang, Z.; Shi, Q.; Cheng, T.; Wang, X.; Zhang, R.; Yu, L. A security-enhanced authentication scheme for quantum-key-distribution (QKD) enabled Internet of vehicles in multi-cloud environment. Veh. Commun. 2024, 48, 100789. [CrossRef]
. Zeydan, E.; Baranda, J.; Mangues-Bafalluy, J. Post-quantum blockchain-based secure service orchestration in multi-cloud networks. IEEE Access 2022, 10, 129520–129530. [CrossRef]
. Ricci, S.; Dobias, P.; Malina, L.; Hajny, J.; Jedlicka, P. Hybrid keys in practice: Combining classical, quantum and post-quantum cryptography. IEEE Access 2024, 12, 23206–23219. [CrossRef]
. Wang, L.J.; Zhang, K.Y.; Wang, J.Y.; Cheng, J.; Yang, Y.H.; Tang, S.B.; Yan, D.; Tang, Y.L.; Liu, Z.; Yu, Y.; et al. Experimental authentication of quantum key distribution with post-quantum cryptography. npj Quantum Inf. 2021, 7, 67. [CrossRef]
. Rani, A.; Ai, X.; Gupta, A.; Adhikari, R.S.; Malaney, R. Combined Quantum and Post-Quantum Security for Earth-Satellite Channels. In Proceedings of the 2025 International Conference on Quantum Communications, Networking, and Computing (QCNC), Nara, Japan, 31 March–2 April 2025; pp. 301–308.
S. R. Veluru, S. Teja Erukude and V. C. Marella, "Multimodal Detection of Fake Reviews using BERT and ResNet-50," 2025 4th International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Tirupur, India, 2025, pp. 877-882, doi: 10.1109/ICIMIA67127.2025.11200892.
Pativada, P. K., Karne, R., & Dudhipala, A. (2025). GNN-based code vulnerability detection using enriched code graphs. In 2025 9th International Conference on Inventive Systems and Control (ICISC) (pp. 1050–1055). IEEE. https://doi.org/10.1109/ICISC65841.2025.11188135
Paladugu N. Zero-Downtime Microservices Deployment Strategies for Mission-Critical Financial Applications. IJERET. 2021 Oct. 30 Nov. 21;2(3):79-88.
Saikrishna Tipparapu, IAM based Audit Framework to enhance and protect the Critical Infrastructurefor Distributed System, Journal of Information Systems Engineering and Management, 2025,10(23s)e-ISSN:2468-4376DOI: https://doi.org/10.52783/jisem.v10i23s.3772
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
