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Enhancing approach using hybrid pailler and RSA for information security in bigdata

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The amount of data processed and stored in the cloud is growing dramatically. The traditional storage devices at both hardware and software levels cannot meet the requirement of the cloud. This fact motivates the need for a platform which can handle this problem. Hadoop is a deployed platform proposed to overcome this big data problem which often uses MapReduce architecture to process vast amounts of data of the cloud system. Hadoop has no strategy to assure the safety and confidentiality of the files saved inside the Hadoop distributed File system (HDFS). In the cloud, the protection of sensitive data is a critical issue in which data encryption schemes plays avital rule. This research proposes a hybrid system between two well-known asymmetric key cryptosystems (RSA, and Paillier) to encrypt the files stored in HDFS. Thus before saving data in HDFS, the proposed cryptosystem is utilized for encrypting the data. Each user of the cloud might upload files in two ways, non-safe or secure. The hybrid system shows higher computational complexity and less latency in comparison to the RSA cryptosystem alone.
Słowa kluczowe
Rocznik
Strony
63--74
Opis fizyczny
Bibliogr. 25 poz., fig., tab.
Twórcy
  • Erbil Polytechnic University, Erbil Technical Engineering College, Department of Information System Engineering, Erbil, Iraq
  • Catholic University in Erbil, Information Technology Department, Erbil, Iraq
  • Erbil Polytechnic University, Erbil Technical Engineering College, Department of Information System Engineering, Erbil, Iraq
Bibliografia
  • [1] Bhardwaj, A., Singh, V. K., Vanraj, & Narayan, Y. (2015). Analyzing BigData with Hadoop Cluster in HDInsight Azure Cloud. Annual IEEE India Conference (INDICON). India: IEEE. doi:10.1109/INDICON.2015.7443472
  • [2] Ahamad, D., Akhtar, M., & Hameed, S. A. (2019). A Review and Analysis of Big Data and MapReduce. International Journal of Advanced Trends in Computer Science and Engineering, 8(1), 1–3.
  • [3] Amrulla, G., Mourya, M., Sanikommu, R. R., & Afroz, A. A. (2018). A Survey of : Securing Cloud Data under Key Exposure. International Journal of Advanced Trends in Computer Science and Engineering, 7(3), 30–33.
  • [4] Bhandarkar, M. (2010). MapReduce programming with apache Hadoop. International Symposium on Parallel & Distributed Processing (IPDPS) (pp. 1-2). Atlanta: IEEE.
  • [5] Chandra, S., Alam, S. S., Paira, S., & Sanyal, G. (2014). A comparative survey of symmetric and asymmetric key cryptography. International Conference on Electronics, Communication and Computational Engineering (ICECCE) (pp. 83–93). IEEE.
  • [6] Chandra, S., Bhattacharyya, S., Paira, S., & Alam, S. S. (2014). A Study and Analysis on Symmetric Cryptography. ICSEMR (pp. 1–8). IEEE.
  • [7] Dean, J., & Ghemawat, S. (2008). MapReduce: Simplified Data Processing on Large Clusters. 6th Symposium on Operating Systems Design and Implementation (pp. 107–113). ACM.
  • [8] Dubey, A. K., Jain, V., & Mittal, A. P. (2015). Stock Market Prediction using Hadoop Map-Reduce Ecosystem. 2nd International Conference on Computing for Sustainable Global Development (pp. 616–621). IEEE.
  • [9] Hilbert, M. (2016). Big Data for Development: A Review of Promises and Challenges. Development Policy Review, 34(1), 135–174.
  • [10] Inukollu, V. N., Arsi, S., & Ravuri, S. R. (2014). Security Issues Associted With big Data In Cloud Computing. International Journal of Network Security & Its Applications (IJNSA), 6(3), 45–56.
  • [11] Ismael, R. S., Youail, R. S., & Kareem, S. W. (2014). Image Encryption by Using RC4 Algorithm. European Academic Research, II(4), 5833–5839.
  • [12] Jam, M. R., Khanli, L. M., Akbari, M. K., & Javan, M. S. (2014 ). A Survey on Security of Hadoop. 4th International Conference on Computer and Knowledge Engineering (ICCKE) (pp. 716–721). IEEE.
  • [13] Kareem, S. W. (2009). Hybrid Public Key Encryption Algorithms For E-Commerce. Erbil: University of Salahaddin–Hawler.
  • [14] Kareem, S. W., & Hussein, Y. T. (2017). Survey and New Security methodology of Routing Protocol in AD-Hoc Network. The 1st International Conference on Information Technology (pp. 452–464). Erbil.
  • [15] Li, B., Wang, M., Zhao, Y., Pu, G., Zhu, H., & Song, F. (2015). Modeling and Verifying Google File System Modeling and Verifying Google File System. 16th International Symposium on High Assurance Systems Engineering (pp. 207–214). IEEE.
  • [16] Mahmoud, H., Hegazy, A., & Khafagy, M. H. (2018). An approach for Big Data Security based on Hadoop Distributed File system. International Conference on Innovative Trends in Computer Engineering (ITCE 2018). Aswan: Aswan University.
  • [17] Merla, P., & Liang, Y. (2017). Data analysis using hadoop MapReduce environment. IEEE International Conference on Big Data (Big Data) (pp. 4783–4785). Boston: IEEE.
  • [18] Motoyama, M., McCoy, D., Levchenko, K., Savage, S., & Voelker, G. M. (2011). An analysis of under-ground forums. ACM SIG- COMM Conference on Internet Measurement Conference IMC '11 (pp. 71–80). New York: ACM.
  • [19] Park, S., & Lee, Y. (2013). Secure Hadoop with Encrypted HDFS. International Conference on Grid and Pervasive Computing (pp. 134–141). Springer.
  • [20] Parmar, R. R., Roy, S., Bhattacharyya, D., Bandyopadhyay, S. K., & Kim, T.-H. (2017). Large-scale encryption in the Hadoop environment: Challenges and solutions. IEEE Access, 5, 7156–7163.
  • [21] Raghad, Z. Y., Kareem, S. W., & Hasan, A. O. (2016). Design Security System Based on AES and MD5 for Smart Card. Sulaimanyia: Charmo university.
  • [22] Shetty, M. M., & Manjaiah, D. H. (2016). Data security in Hadoop distributed file system. IEEE Int. Conf. Emerg. Technol. Trends Comput. Commun. Electr. Eng. ICETT 2016 (pp. 939–944). IEEE.
  • [23] Usama, M., & Zakaria, N. (2017). Chaos-Based Simultaneous Compression and Encryption for Hadoop. PLoS One.
  • [24] Yang, Ch., Lin, W., & Liu, M. (2013). A Novel Triple Encryption Scheme for Hadoop-based Cloud Data Security. Fourth International Conference on Emerging Intelligent Data and Web Technologies (pp. 437–442). IEEE.
  • [25] Zhou, H., & Wen, Q. (2014). A new solution of data security accessing for Hadoop based on CP-ABE. 5th International Conference on Software Engineering and Service Science (pp. 525–528). IEEE.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9ff3eec7-13ad-4c14-acbf-8c118a50fd37
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