Decentralised Storage Network by Using Block-Chain
DOI:
https://doi.org/10.48001/jowacs.2024.2125-30Keywords:
Blockchain, Decentralization, Digitization, Identity management, Network security, Practical implementation, Scalability, Smart contracts, Threat detection, VulnerabilitiesAbstract
This paper explores the intersection of network security and blockchain technology in the context of today's digital era. It begins by acknowledging the vulnerabilities and threats contemporary networks face, including data breaches and denial-of-service attacks. The paper then delves into the foundational principles of blockchain, highlighting its decentralization, consensus mechanisms, cryptographic encryption, and immutability as key attributes that can enhance network security The central idea presented is the potential of blockchain to revolutionize network security. It discusses how blockchain can be integrated into network architecture to achieve secure and transparent identity management, combat identity fraud, automate network processes through smart contracts, and enhance real-time threat detection and response. However, the paper also recognizes challenges such as scalability, interoperability, and energy efficiency when implementing blockchain in secure networks and suggests ongoing research efforts and potential solutions to make this integration more practical.
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Batchu, S., Henry, O. S., & Hakim, A. A. (2021). A novel decentralized model for storing and sharing neuroimaging data using ethereum blockchain and the interplanetary file system. International Journal of Information Technology, 13, 2145-2151.
https://doi.org/10.1007/s41870-021-00746-3.
Bere, S. S., Shukla, G. P., Khan, V. N., Shah, A. M., & Takale, D. G. (2022). Analysis of students performance prediction in online courses using machine learning algorithms.Neuroquantology, 20(12), 13. https://doi.org/10.14704/Nq.2022.20.12.Nq77002
Chiwariro, R., & . N, T. (2022). Quality of service aware routing protocols in wireless multimedia sensor networks: survey. International Journal of Information Technology, 14(2), 789-800.
https://doi.org/10.1007/s41870-020-00478-w.
Dattatray, M. T., & Amrit, M. P. (2014). A study of fault management algorithm and recover the faulty node using the FNR algorithms for wireless sensor network. International Journal of Engineering Research and General Science, 2(6), 590-595.
Javed, M. U., Rehman, M., Javaid, N., Aldegheishem, A., Alrajeh, N., & Tahir, M. (2020). Blockchain-based secure data storage for distributed vehicular networks. Applied Sciences, 10(6), 2011.
https://doi.org/10.3390/app10062011.
Jiang, T., Fang, H., & Wang, H. (2018). Blockchain-based internet of vehicles: Distributed network architecture and performance analysis. IEEE Internet of Things Journal, 6(3), 4640-4649.
https://doi.org/10.1109/JIOT.2018.2874398.
Kadam, S. U., Dhede, V. M., Khan, V. N., Raj, A., & Takale, D. G. (2022). Machine learning methode for automatic potato disease detection. Neuro Quantology, 20(16), 2102-2106.
https://doi.org/10.48047/NQ.2022.20.16.NQ880300.
Kadam, S. U., Khan, V. N., Singh, A., Takale, D. G., & Galhe, D. S. (2022). Improve the performance of non-intrusive speech quality assessment using machine learning algorithms. NeuroQuantology, 20(10), 12937. https://doi.org/10.14704/nq.2022.0.10.NQ551254.
Li, D., Wong, W. E., Zhao, M., & Hou, Q. (2020, December). Secure storage and access for task-scheduling schemes on consortium blockchain and interplanetary file system. In 2020 IEEE 20th International Conference on Software Quality, Reliability and Security Companion (QRS-C) (pp. 153-159). IEEE.
https://doi.org/10.1109/QRS-C51114.2020.00035.
Mandala, D., Du, X., Dai, F., & You, C. (2008). Load balance and energy efficient data gathering in wireless sensor networks. Wireless Communications and Mobile Computing, 8(5), 645-659.
https://doi.org/10.1002/wcm.492.
Mendu, M., Krishna, B., Mohmmad, S., Sharvani, Y., & Reddy, C. V. K. (2020, December). Secure deployment of decentralized cloud in blockchain environment using inter-planetary file system. In IOP Conference Series: Materials Science and Engineering (Vol. 981, No. 2, p. 022037). IOP Publishing.
https://doi.org/10.1088/1757-899X/981/2/022037.
Mittal, N., Singh, U., & Sohi, B. S. (2017). A stable energy efficient clustering protocol for wireless sensor networks. Wireless Networks, 23, 1809-1821.
https://doi.org/10.1007/s11276-016-1255-6.
Rahman, M. A., Rashid, M. M., Barnes, S. J., & Abdullah, S. M. (2019, August). A blockchain-based secure internet of vehicles management framework. In 2019 UK/China Emerging Technologies (UCET) (pp. 1-4). IEEE. https://doi.org/10.1109/UCET.2019.8881874.
Raut, R., Borole, Y., Patil, S., Khan, V., & Takale, D. G. (2022). Skin disease classification using machine learning algorithms. NeuroQuantology, 20(10), 9624-9629.
https://doi.org/10.14704/nq.2022.20.10.NQ55940.
Shende, M. S. S. (2023). A review on wireless sensor network: Its applications and challenges. International Journal of Computational Research in Engineering and Science, 1(01), 18-25.
https://ijcres.org/index.php/1/article/view/8.
Takale, D. D., & Khan, V. (2023). Machine learning techniques for routing in wireless sensor network. International Journal of Research and Analytical Reviews, 10(1).
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4394967.
Takale, D. D., Sharma, D. Y. K., & SN, P. (2019). A review on data centric routing for wireless sensor network. Journal of Emerging Technologies and Innovative Research (JETIR), 6(1).
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4416491.
Takale, D. G., Gunjal, S. D., Khan, V. N., Raj, A., & Guja, S. N. (2022). Road accident prediction model using data mining techniques. NeuroQuantology, 20(16), 2904.
https://doi.org/10.48047/NQ.2022.20.16.NQ880299.
Takale, D. G., Mahalle, P. N., Sakhare, S. R., Gawali, P. P., Deshmukh, G., Khan, V., ... & Maral, V. B. (2023, August). Analysis of clinical decision support system in healthcare industry using machine learning approach. In International Conference on ICT for Sustainable Development (pp. 571-587). Singapore: Springer Nature Singapore.
https://doi.org/10.1007/978-981-99-5652-4_51.
Zhang, H., Liu, J., Zhao, H., Wang, P., & Kato, N. (2020). Blockchain-based trust management for internet of vehicles. IEEE Transactions on Emerging Topics in Computing, 9(3), 1397-1409.
https://doi.org/10.1109/TETC.2020.3033532.
Zhang, L., Luo, M., Li, J., Au, M. H., Choo, K. K. R., Chen, T., & Tian, S. (2019). Blockchain based secure data sharing system for Internet of vehicles: A position paper. Vehicular Communications, 16, 85-93. https://doi.org/10.1016/j.vehcom.2019.03.003.