Refine your search
Collections
Co-Authors
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Shrivastava, Gaurav
- Secure Storage and Data Sharing Scheme Using Private Blockchain-Based HDFS Data Storage for Cloud Computing
Abstract Views :112 |
PDF Views:1
Authors
Affiliations
1 Department of Computer Science and Engineering, SAGE University, Indore, Madhya Pradesh, IN
1 Department of Computer Science and Engineering, SAGE University, Indore, Madhya Pradesh, IN
Source
International Journal of Computer Networks and Applications, Vol 10, No 1 (2023), Pagination: 28-38Abstract
The storage of a vast quantity of data in the cloud, which is then delivered via the internet, enables Cloud Computing to make doing business easier by providing smooth access to the data and eliminating device compatibility limits. Data that is in transit, on the other hand, may be intercepted by a man-in-the-middle attack, a known plain text assault, a selected cypher text attack, a related key attack, or a pollution attack. Uploading data to a single cloud might, as a result, increase the likelihood that the secret data would be damaged. A distributed file system extensively used in huge data analysis for frameworks such as Hadoop is known as the Hadoop Distributed File System, more commonly referred to as HDFS. Because with HDFS, it is possible to manage enormous volumes of data while using standard hardware that is not very costly. On the other hand, HDFS has several security flaws that might be used for malicious purposes. This highlights how critical it is to implement stringent security measures to make it easier for users to share files inside Hadoop and to have a reliable system in place to validate the shared files' validity claims. The major focus of this article is to discuss our efforts to improve the security of HDFS by using an approach made possible by blockchain technology (hereafter referred to as BlockHDFS). To be more precise, the proposed BlockHDFS uses the Hyperledger Fabric platform, which was developed for business applications, to extract the most value possible from the data inside files to provide reliable data protection and traceability in HDFS. In the results section, the performance of AES is superior to that of other encryption algorithms because it ranges from 1.2 milliseconds to 1.9 milliseconds. In contrast, DES ranges from 1.3 milliseconds to 3.1 milliseconds, three milliseconds to 3.6 millimetres, RC2 milliseconds to 3.9 milliseconds, and RSA milliseconds to 1.4 milliseconds, with data sizes ranging from 910 kilos.Keywords
Cloud Computing, Hadoop Distributed File System, Blockchain, Authenticity, Data Security, DES, AES.Full Text
References
- G. Kumar et al., "A Novel Framework for Fog Computing: Lattice-Based Secured Framework for Cloud Interface," in IEEE Internet of Things Journal, vol. 7, no. 8, pp. 7783-7794, Aug. 2020, doi: 10.1109/JIOT.2020.2991105.
- X. Liu, G. Yang, Y. Mu and R. H. Deng, "Multi-User Verifiable Searchable Symmetric Encryption for Cloud Storage," in IEEE Transactions on Dependable and Secure Computing, vol. 17, no. 6, pp. 1322-1332, 1 Nov.-Dec. 2020, doi: 10.1109/TDSC.2018.2876831.
- Benet, J. Ipfs-content addressed, versioned, p2p file system. arXiv 2014, arXiv:1407.3561.
- J. Wei, X. Chen, X. Huang, X. Hu and W. Susilo, "RS-HABE: Revocable-Storage and Hierarchical Attribute-Based Access Scheme for Secure Sharing of e-Health Records in Public Cloud," in IEEE Transactions on Dependable and Secure Computing, vol. 18, no. 5, pp. 2301-2315, 1 Sept.-Oct. 2021, doi: 10.1109/TDSC.2019.2947920.
- H. Wang, L. Feng, Y. Ji, B. Shao and R. Xue, "Toward Usable Cloud Storage Auditing, Revisited," in IEEE Systems Journal, vol. 16, no. 1, pp. 693-700, March 2022, doi: 10.1109/JSYST.2021.3055021.
- Apache Hadoop, URL, http://hadoop.apache.org, 2006.
- K. Shvachko, H. Kuang, S. Radia, R. Chansler, The hadoop distributed file system, in: 2010 IEEE 26th Sym- Posium on Mass Storage Systems and Technologies (MSST); 3–7 May 2010; Incline Village, NV, USA, IEEE, Piscataway, NJ, USA, 2010, pp. 1–10.
- S.A. Weil, S.A. Brandt, E.L. Miller, D.D.E. Long, C. Maltzahn, Ceph: a scalable, high performance dis- tributed file system, in: Proceedings of the 7th Symposium on Operating Systems Design and Implementation, OSDI '06; 6–8 Nov 2006; Seattle, WA, USA, USENIX Association, Berkeley, CA, USA, 2006, pp. 307–320.
- F. Schmuck, R. Haskin, Gpfs: a shared-disk file system for large computing clusters, in: Proceedings of the 1st USENIX Conference on File and Storage Technologies, FAST '02; 28–30 Jan 2002; Monterey, CA, USA, USENIX Association, Berkeley, CA, USA, 2002.
- C. Ungureanu, B. Atkin, A. Aranya, et al., HydraFS: A high-throughput file system for the hydrastor content-addressable storage system, in: Proceedings of the 8th USENIX Conference on File and Storage Technologies, FAST'10; 23–26 Feb 2010; San Jose, CA, USA, USENIX Association, Berkeley, CA, USA, 2010, pp. 225–239.
- J. Dean, S. Ghemawat, Mapreduce: simplified data processing on large clusters, Commun. ACM 51 (1) (2008) 107–113.
- M. Zaharia, R.S. Xin, P. Wendell, T. Das, M. Armbrust, A. Dave, X. Meng, J. Rosen, S. Venkataraman, M.J. Franklin, et al., Apache spark: a unified engine for big data processing, Commun. ACM 59 (11) (2016) 56–65.
- X. Chen, L. Hu, L. Liu, J. Chang and D. L. Bone, "Breaking Down Hadoop Distributed File Systems Data Analytics Tools: Apache Hive vs. Apache Pig vs. Pivotal HWAQ," 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), 2017, pp. 794-797, doi: 10.1109/CLOUD.2017.117.
- M.N. Vora, Hadoop-hbase for large-scale data, in: Proceedings of 2011 International Conference on Computer Science and Network Technology; 24–26 Dec 2011; Harbin, China, IEEE, Piscataway, NJ, USA, 2011, pp. 601–605.
- F. Shahid, H. Ashraf, A. Ghani, S. A. K. Ghayyur, S. Shamshirband and E. Salwana, "PSDS–Proficient Security Over Distributed Storage: A Method for Data Transmission in Cloud," in IEEE Access, vol. 8, pp. 118285-118298, 2020, doi: 10.1109/ACCESS.2020.3004433.
- J. Tang, J. Nie, Z. Xiong, J. Zhao, Y. Zhang and D. Niyato, "Slicing-Based Reliable Resource Orchestration for Secure Software-Defined Edge-Cloud Computing Systems," in IEEE Internet of Things Journal, vol. 9, no. 4, pp. 2637-2648, 15 Feb.15, 2022, doi: 10.1109/JIOT.2021.3107490.
- A. Saini, Q. Zhu, N. Singh, Y. Xiang, L. Gao and Y. Zhang, "A Smart-Contract-Based Access Control Framework for Cloud Smart Healthcare System," in IEEE Internet of Things Journal, vol. 8, no. 7, pp. 5914-5925, 1 April1, 2021, doi: 10.1109/JIOT.2020.3032997.
- S. Sengupta and S. S. Bhunia, "Secure Data Management in Cloudlet Assisted IoT Enabled e-Health Framework in Smart City," in IEEE Sensors Journal, vol. 20, no. 16, pp. 9581-9588, 15 Aug.15, 2020, doi: 10.1109/JSEN.2020.2988723.
- Z. Su et al., "Secure and Efficient Federated Learning for Smart Grid With Edge-Cloud Collaboration," in IEEE Transactions on Industrial Informatics, vol. 18, no. 2, pp. 1333-1344, Feb. 2022, doi: 10.1109/TII.2021.3095506.
- S. Srinivasan, "Cloud load balancing: Blockchain deployment at integrated DopCloud synthesis on Healthcare data," 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), 2020, pp. 364-369, doi: 10.1109/ICSSIT48917.2020.9214084.
- G. Senthilkumar and M. P. Chitra, "A Novel hybrid heuristic-metaheuristic Load balancing algorithm for Resource allocationin IaaS-cloud computing," 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), 2020, pp. 351-358, doi: 10.1109/ICSSIT48917.2020.9214280.
- J. Cai, Y. Hu and Y. Li, "Research on the Method of Building a Secure Cloud Storage Platform," 2022 3rd International Conference on Electronic Communication and Artificial Intelligence (IWECAI), 2022, pp. 17-20, doi: 10.1109/IWECAI55315.2022.00011.
- B. Tang and G. Fedak, "WukaStore: Scalable, Configurable and Reliable Data Storage on Hybrid Volunteered Cloud and Desktop Systems," in IEEE Transactions on Big Data, vol. 8, no. 1, pp. 85-98, 1 Feb. 2022, doi: 10.1109/TBDATA.2017.2758791.
- J. Li, H. Yan and Y. Zhang, "Efficient Identity-Based Provable Multi-Copy Data Possession in Multi-Cloud Storage," in IEEE Transactions on Cloud Computing, vol. 10, no. 1, pp. 356-365, 1 Jan.-March 2022, doi: 10.1109/TCC.2019.2929045.
- Gupta, A. K. Singh, C. -N. Lee and R. Buyya, "Secure Data Storage and Sharing Techniques for Data Protection in Cloud Environments: A Systematic Review, Analysis, and Future Directions," in IEEE Access, vol. 10, pp. 71247-71277, 2022, doi: 10.1109/ACCESS.2022.3188110.
- J. -N. Liu et al., "Enabling Efficient, Secure and Privacy-Preserving Mobile Cloud Storage," in IEEE Transactions on Dependable and Secure Computing, vol. 19, no. 3, pp. 1518-1531, 1 May-June 2022, doi: 10.1109/TDSC.2020.3027579.
- X. Li, T. Xiang, Y. Mu, F. Guo and Z. Yao, "C-Wall: Conflict-Resistance in Privacy-Preserving Cloud Storage," in IEEE Transactions on Cloud Computing, doi: 10.1109/TCC.2022.3171772.
- M. A. M. Ahsan, I. Ali, M. Imran, M. Y. I. B. Idris, S. Khan and A. Khan, "A Fog-Centric Secure Cloud Storage Scheme," in IEEE Transactions on Sustainable Computing, vol. 7, no. 2, pp. 250-262, 1 April-June 2022, doi: 10.1109/TSUSC.2019.2914954.
- K. Lee, J. Kim, J. Kwak and Y. Kim, "Dynamic Multi-Resource Optimization for Storage Acceleration in Cloud Storage Systems," in IEEE Transactions on Services Computing, doi: 10.1109/TSC.2022.3173333.
- G. Revathy, P. Muruga Priya, R. Saranya and C. Ramchandran, "Cloud Storage and Authenticated Access For Intelligent Medical System," 2022 6th International Conference on Computing Methodologies and Communication (ICCMC), 2022, pp. 53-56, doi: 10.1109/ICCMC53470.2022.9753765.
- C. Liang, L. Deng, J. Zhu, Z. Cao and C. Li, "Cloud Storage I/O Load Prediction Based on XB-IOPS Feature Engineering," 2022 IEEE 8th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), 2022, pp. 54-60, doi: 10.1109/BigDataSecurityHPSCIDS54978.2022.00020.
- Y. Yang, Y. Chen, F. Chen and J. Chen, "An Efficient Identity-Based Provable Data Possession Protocol With Compressed Cloud Storage," in IEEE Transactions on Information Forensics and Security, vol. 17, pp. 1359-1371, 2022, doi: 10.1109/TIFS.2022.3159152.
- V. J. Sosa-Sosa, A. Barron, J. L. Gonzalez-Compean, J. Carretero and I. Lopez-Arevalo, "Improving Performance and Capacity Utilisation in Cloud Storage for Content Delivery and Sharing Services," in IEEE Transactions on Cloud Computing, vol. 10, no. 1, pp. 439-450, 1 Jan.-March 2022, doi: 10.1109/TCC.2020.2968444.
- J. Ni, K. Zhang, Y. Yu and T. Yang, "Identity-Based Provable Data Possession From RSA Assumption for Secure Cloud Storage," in IEEE Transactions on Dependable and Secure Computing, vol. 19, no. 3, pp. 1753-1769, 1 May-June 2022, doi: 10.1109/TDSC.2020.3036641.
- Z. Ullah, B. Raza, H. Shah, S. Khan and A. Waheed, "Towards Blockchain-Based Secure Storage and Trusted Data Sharing Scheme for IoT Environment," in IEEE Access, vol. 10, pp. 36978-36994, 2022, doi: 10.1109/ACCESS.2022.3164081.
- K. B. Jyothilakshmi, V. Robins, and A. S. Mahesh, "A comparative analysis between hyperledger fabric and ethereum in medical sector: A systematic review," in Sustainable Communication Networks and Application. Singapore: Springer, 2022, pp. 67–86.
- G Shrivastava and S. Patel, “Hybrid Confidentiality Framework for Secured Cloud Computing” in 2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT), 07-09 October 2022, 10.1109/GCAT55367.2022.9972165.