BlockStream Solutions: Enhancing Cloud Storage Efficiency and Transparency through Blockchain Technology
International Journal of Electrical and Electronics Engineering |
© 2024 by SSRG - IJEEE Journal |
Volume 11 Issue 7 |
Year of Publication : 2024 |
Authors : K. Rama Krishna, M. Pounambal, Jaibir Singh, Gunti Surendra, Syed Muqthadar Ali, B. Mallikarjuna Reddy |
How to Cite?
K. Rama Krishna, M. Pounambal, Jaibir Singh, Gunti Surendra, Syed Muqthadar Ali, B. Mallikarjuna Reddy, "BlockStream Solutions: Enhancing Cloud Storage Efficiency and Transparency through Blockchain Technology," SSRG International Journal of Electrical and Electronics Engineering, vol. 11, no. 7, pp. 134-147, 2024. Crossref, https://doi.org/10.14445/23488379/IJEEE-V11I7P111
Abstract:
This paper introduces the BlockStream model, a novel integration of blockchain technology into cloud storage systems aimed at addressing the core challenges of security, efficiency, and transparency. The research methodology encompasses a comprehensive system design and implementation, utilizing synthetic datasets for performance evaluation against traditional cloud storage solutions. Key findings reveal that the BlockStream model significantly enhances storage efficiency, with data deduplication rates and storage space utilization surpassing existing models by up to 15%. Moreover, it achieves a notable reduction in data retrieval times, improving by 7.14% over the most efficient traditional systems, and demonstrates superior security capabilities, particularly in resistance to DDoS attacks and unauthorized access prevention, markedly outperforming the baseline models. The significance of this research lies in its potential to revolutionize cloud storage paradigms, offering a scalable, secure, and user-centric data management solution. Quantitatively, the BlockStream model not only reduces average data retrieval times from 400ms to 320ms compared to current leading solutions but also elevates the security and robustness of cloud storage systems to levels previously unattained, marking a significant advancement in the field. These enhancements, underpinned by the decentralized, immutable, and transparent nature of blockchain, present a compelling case for the integration of blockchain technology in improving the architecture and operation of cloud storage systems.
Keywords:
Blockchain, Cloud storage, Data integrity, Storage efficiency, Security enhancements, Performance evaluation.
References:
[1] Amir Javadpour et al., “Encryption as a Service for IoT: Opportunities, Challenges and Solutions,” IEEE Internet of Things Journal, vol. 11, no. 5, pp. 7525-7558, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Md Habib Ullah et al., “Quantum Computing for Smart Grid Applications,” IET Generation, Transmission & Distribution, vol. 16, no. 21, pp. 4239-4257, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Md. Masudul Islam, M.M. Fazle Rabbi, and Mijanur Rahaman, “A Review on Integration of Quantum Processor Services with Recursive Quantum Network in Cloud System,” Global Journal of Computer Science and Technology, vol. 16, 2016.
[Google Scholar] [Publisher Link]
[4] Maanak Gupta et al., Future Connected Technologies: Growing Convergence and Security Implications, CRC Press, 2023.
[Google Scholar] [Publisher Link]
[5] T. Swamy, and Sunil Vijaya Kumar Gaddam, “Leveraging Quantum Computing for Enhanced Cryptographic Protocols in Cloud Security,” International Journal of Computer Engineering in Research Trends, vol. 11, no. 5, pp. 1-8, 2024.
[Publisher Link]
[6] Elhadj Benkhelifa, Lokhande Gaurav, and Vidya Sagar S.D., “BioShieldNet: Advanced Biologically Inspired Mechanisms for Strengthening Cybersecurity in Distributed Computing Environments,” International Journal of Computer Engineering in Research Trends, vol. 11, no. 3, pp. 1-9, 2024.
[Publisher Link]
[7] K. Samunnisa, and Sunil Vijaya Kumar Gaddam, “Blockchain-Based Decentralized Identity Management for Secure Digital Transactions,” Synthesis: A Multidisciplinary Research Journal, vol. 1, no. 2, pp. 22-29, 2023.
[Publisher Link]
[8] A. Mallareddy, R. Sridevi, and C.G.V. N. Prasad, “Enhanced P-Gene Based Data Hiding for Data Security in Cloud,” International Journal of Recent Technology and Engineering, vol. 8, no. 1, pp. 2086-2093, 2019.
[Google Scholar] [Publisher Link]
[9] Ch G.V.N. Prasad et al., “Edge Computing and Blockchain in Smart Agriculture Systems,” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 10, no. 1, pp. 265-274, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Sagar Mekala et al., “EASND: Energy Adaptive Secure Neighbour Discovery Scheme for Wireless Sensor Networks,” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 11, no. 5s, pp. 446-458, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[11] M. Jahir Pasha et al., “LRDADF: An AI Enabled Framework for Detecting Low-Rate DDoS Attacks in Cloud Computing Environments,” Measurement: Sensors, vol. 28, pp. 1-11, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Sagar Mekala et al., “Machine Learning and Fuzzy Logic Based Intelligent Algorithm for Energy Efficient Routing in Wireless Sensor Networks,” Multi-Disciplinary Trends in Artificial Intelligence, pp. 523-533, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[13] J. Mahalakshmi et al., “Enhancing Cloud Security with AuthPrivacyChain: A Blockchain-Based Approach for Access Control and Privacy Protection,” International Journal of Intelligent Systems and Applications in Engineering, vol. 11, no. 6s, pp. 370-384, 2023.
[Google Scholar] [Publisher Link]
[14] Kashvi Gupta et al., “SecureChain: A Novel Blockchain Framework for Enhancing Mobile Device Integrity through Decentralized IMEI Verification,” Frontiers in Collaborative Research, vol. 1, no. 1, pp. 1-11, 2023.
[Google Scholar] [Publisher Link]
[15] G. Ravikumar et al., “Cloud Host Selection Using Iterative Particle-Swarm Optimization for Dynamic Container Consolidation,” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 10, no. 1s, pp. 247-253, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Gangolu Yedukondalu et al., “MOCF: A Multi-Objective Clustering Framework Using an Improved Particle Swarm Optimization Algorithm,” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 10, no. 10, pp. 143-154, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[17] E.V.N. Jyothi et al., “A Graph Neural Networkbased Traffic Flow Prediction System with Enhanced Accuracy and Urban Efficiency,” Journal of Electrical Systems, vol. 19, no. 4, pp. 336-349, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Claus Pahl et al., “Enhancing Cloud Service Selection and Orchestration with DALMOCS: A Dynamic Adaptive Learning and Multi-Criteria Decision Analysis Approach,” International Journal of Computer Engineering in Research Trends, vol. 11, no. 2, pp. 18-26, 2024.
[Publisher Link]
[19] Hoang Phuc Hau Luu, Abdlehak Sakhi, and Mukhlisulfatih Latief, “Optimizing Group Management and Cryptographic Techniques for Secure and Efficient MTC Communication,” International Journal of Computer Engineering in Research Trends, vol. 11, no. 2, pp. 1-8, 2024.
[Publisher Link]
[20] N’guessan Patrice Akoguhi, and M. Bhavsingh, “Blockchain Technology in Real Estate: Applications, Challenges, and Future Prospects,” International Journal of Computer Engineering in Research Trends, vol. 10, no. 9, pp. 16-21, 2023.
[CrossRef] [Publisher Link]
[21] Mohammed Adam Kunna Azrag et al., “A Novel Blockchain-Based Framework for Enhancing Supply Chain Management,” International Journal of Computer Engineering in Research Trends, vol. 10, no. 6, pp. 22-28, 2023.
[CrossRef] [Publisher Link]
[22] Leela Mahesh Reddy, and K. Madhavi, “Blockchain Split-Join Architecture: A Novel Framework for Improved Transaction Processing,” Frontiers in Collaborative Research, vol. 1, no. 3, pp. 20-29, 2023.
[Publisher Link]
[23] Shuroq Jawad Mahdi, “Preventing from Collusion Data Sharing Mechanism for Dynamic Group in the Cloud,” Macaw International Journal of Advanced Research in Computer Science and Engineering, vol. 2, no. 7, pp. 113-118, 2016.
[Publisher Link]
[24] Venna Sujith Reddy, and K. Venkatesh Sharma, “Advancements in Automated Video Analysis Selective Scanning for Person of Interest Recognition,” Macaw International Journal of Advanced Research in Computer Science and Engineering, vol. 9, no. 12, pp. 1-8, 2023.
[Google Scholar] [Publisher Link]
[25] J. Keziya Rani, “Green Computing Paradigms towards Energy Conservation and E-Waste Minimization,” Macaw International Journal of Advanced Research in Computer Science and Engineering, vol. 2, no. 9, pp. 1-5, 2016.
[Google Scholar] [Publisher Link]
[26] S. Kiran, and Sreekanth Rallapall, “Innovative Blockchain Split-Join Architecture for Optimized Data Management,” Synthesis: A Multidisciplinary Research Journal, vol. 1, no. 3, pp. 1-11, 2024.
[Google Scholar] [Publisher Link]
[27] Kan Yang, and Xiaohua Jia, “An Efficient and Secure Dynamic Auditing Protocol for Data Storage in Cloud Computing,” IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 9, pp. 1717-1726, 2012.
[CrossRef] [Google Scholar] [Publisher Link]