Emergency Management

Emergency Management

A New Model of the Security Operations Center (SOC) in the Banking Industry

Document Type : Original Article

Authors
Seyed Zin El Abidine Hosseini 1
Mansour Esmaeilpour 2
Alireza Slambolchi 3
Mohammad Reza Rabieh Mondjin 4
Alireza Amirkabiri 4
1 PhD. Student, Dept. of Information Technology Management, Islamic Azad University, Hamedan Branch, Hamedan, Iran
2 Assoc. Prof., Dept. of Computer Engineering, Islamic Azad University, Hamedan Branch, Hamedan, Iran
3 Assist. Prof., Dept. of Management, Islamic Azad University, Hamedan Branch, Hamedan, Iran
4 Assist. Prof., Dept. of Management, Islamic Azad University, Central Tehran Branch, Tehran, Iran
Abstract
One of the most important security challenges in e-banking security centers is the inability of the internet to deal with attacks. These attacks are easily implemented and can be controlled locally or remotely. Most of these attacks are successful in reaching the main targets of the attack and bring the attacker to their desires. The reason for this is that there are many mechanisms for launching attacks based on the characteristics of the victim's server, which makes it impossible to provide a comprehensive defense solution against the attacks. Several strategies have been proposed to identify and deal with these attacks. In this paper, a combination of algorithm for selecting genetic features and machine learning methods, including decision tree algorithm, deep neural network and KNN, are presented. Provide guidelines for validation, the results obtained with other techniques such as machine learning techniques and combined with other optimization methods are compared and evaluated. In this research, 10% of KDD Cup 99 dataset for simulation has been used. First, in the preprocessing of data, the values of all attributes are converted to numbers, and the output characteristic values are changed to two values of zero and one. The results of the research indicate that the accuracy of the proposed strategy for detecting intruders compared to other recent methods is about 5%.
Subjects

  1. 1-“شرکت بهین راهکار توسعه پیشرو,” 1399. [درون‌خطی. [Available: http://www.behinrahkar.com.

    2- “پروژه معماری و طراحی مرکز عملیات امنیت بومی مبتنی بر راهکارهای متن‌باز,” 1388. [درون‌خطی[. Available: http://www.ic4i.ir.

    1. E. ElFgee and A. Arara, "Technical Requirements of New Framework for GPRS Security Protocol Mobile Banking Application," Procedia Computer Science, p. Procedia Computer Science, 2014.
    2. S. Bojjagani and V. N. Sastry, "Stamba: Security testing for Android mobile banking apps," In Advances in Signal Processing and Intelligent Recognition Systems, pp. pp. 671-683, 2016.
    3. R. K. Rehiman and S. Veni, "A secure authentication infrastructure for IoT Enabled smart mobile devices–An Initial Prototype," Indian Journal of Science and Technology, p. 9(9), 2016.
    4. N. Thompson, L. T. McGill and X. Wang, "“Security begins at home”: Determinants of home computer and mobile device security behavior," computers & security, pp. 70, 376-391, 2017.
    5. S. Bhatnagar, Y. Malik and S. Butakov, "Analysing Data Security Requirements of Android Mobile Banking Application," in In International Conference on Intelligent, Secure, and Dependable Systems in Distributed and Cloud Environments, 2018.
    6. S. Chen,. Meng, T. Su, L. Fan, Y. Xue, Y. Liu and S. Hao, "AUSERA: Large-Scale Automated Security Risk Assessment of Global Mobile Banking Apps," arXiv preprint arXiv, p. 1805.05236, 2018.
    7. H. K. Yeh, "A secure transaction scheme with certificateless cryptographic primitives for IoT-based mobile payments," IEEE Systems Journal, pp. 12(2), 2027-2038, 2018.
    8. D. Saurabh, Y. Qiang and S. Srinivas, "A Machine Learning Based Intrusion Detection Scheme for Data Fusion in Mobile Clouds Involving Heterogeneous Client Networks," Information Fusion, 2018.
    9. S. Sakr, A. Liu, M. D. Batista and M. Alomari, "A survey of large scale data management approaches in cloud environments," IEEE Communications Surveys & Tutorials, pp. 13(3), 311-336, 2011.
    10. 2021. [Online]. Available: https://www.tutorialspoint.com/cryptography/advanced_encryption_standard.htm.
    11. H. M. Mokhtar, O. Ossama and M. E.El-Sharkawi, "An extended k-means technique for clustering moving objects," Egyptian Informatics Journal, pp. 45-51, 2011.
    12. S. N. Sivanandam and S. N. Deepa, "Genetic algorithm optimization problems," In Introduction to Genetic Algorithms, pp. pp. 165-209, 2008.
    13. D. S. Weile and E. Michielssen, "Genetic algorithm optimization applied to electromagnetics: A review," IEEE Transactions on Antennas and Propagation, pp. 45(3), 343-353, 1997.
    14. K. Indira and S. Kanmani, "Association rule mining using genetic algorithm: The role of estimation parameters," in International Conference on Advances in Computing and Communications, Berlin, Heidelberg, 2011.
    15. D. E. Goldberg, Genetic Algorithm in Search, Optimization & Machine Learning, New York: Addison-Wesely, 1989.
    16. N. Jain and V. Srivastava, "Data Mining techniques: A survey paper.IJRET," International Journal of Research in Engineering and Technology, pp. pp.19-23, 2013.
    17. T. Shang, X. Xia and J. Zheng, "MIME-KNN: Improve KNN Classifier Performance Include رده‌بندی Accuracy and Time Consumption‏," DEStech Transactions on Computer, 2018.
    18. S. Yang, H. Jian, Z. Ding, Z. Hongyuan and G. C. Lee, IKNN: Informative K-Nearest Neighbor Pattern Classification, Berlin Heidelberg: Springer-Verlag, 2007.
    19. Y. LeCun, Y. Bengio and G. Hinton, "Deep learning," nature, pp. 521(7553), 436, 2015.
    20. M. G. Raman, N. Somu, K. Kirthivasan, R. Liscano and V. S. Sriram, "An efficient intrusion detection system based on hypergraph-Genetic algorithm for parameter optimization and feature selection in support vector machine," Knowledge-Based Systems, pp. 134, 1-12, 2017.

    23- ه. مینتربرگ، ب. آلستراند و ژ. لمپل، جنگل استراتژی (کارآفرینی در قالب یک مکتب), تهران: جاجرمی، 1384.

    1. B. Schwenker and T. Wulf, Scenario-based Strategic Planning: Developing Strategies in an Uncertain World, Springer, 2013.

    25- ع. آذر، آمار و کاربرد آن در مدیریت، تهران: سمت، 1390.

    1. M. Portet, Competitive strategy: Techniques for analyzing industries and competitors, New York: Simon and Schuster, 2008.
    2. G. Johnson, K. Scholes and R. Whittington, Exploring Corporate Strategy, 8th ed., Londen: Financial Times Prentice Hall, 2008.
Emergency Management
Volume 12, Economic Defense Special Issue
Economic Defense Special Issue
February 2024
Pages 34-64

  • Receive Date 19 February 2022
  • Revise Date 22 May 2023
  • Accept Date 05 July 2023