Cyber security operations centre ML framework for the needs of the users

Venkata Ravi Kiran Kolla

Abstract


To ensure an organization's cyber security, a SIEM (Security Information and Event Management) system is generally in place to standardize security events from multiple preventative technologies and signal alarms. Security operation center (SOC) analysts analyze the alerts to determine whether or not the threat is genuine. However, the sheer volume of warnings is deafening, with the vast majority of them being false positives that strain the SOC's ability to process them all. As a result, harmful assaults and infected hosts may go undetected. SOC analysts' productivity can be improved by reducing the number of false positives in their reports using machine learning. In this study, we create a cyber security operation center user-centric machine learning framework in a real-world corporate setting. To develop a successful machine learning system, we cover the usual data sources in SOC, their workflow, and how to use and analyze these data sets.

References


X. Li and B. Liu, "Learning to classify text using positive and unlabeled data", Proceedings of the 18th international joint conference on Artificial intelligence, 2003.

A. L. Buczak and E. Guven, "A survey of data mining and machine learning methods for cyber security intrusion detection", IEEE Communications Surveys & Tutorials, vol. 18.2, pp. 1153-1176, 2015.

S. Choudhury and A. Bhowal, "Comparative analysis of machine learning algorithms along with classifiers for network intrusion detection", Smart Technologies and Management for Computing Communication Controls Energy and Materials (ICSTM), 2015.

P. Fabian, V. Gaël, G. Alexandre, M. Vincent, T. Bertrand, G. Olivier et al., "Scikit-learn: Machine Learning in Python", Journal of Machine Learning Research, pp. 2825-2830, 2011.

K. M. Lee, K. Y. Kim and J. S. Yoo, "Autonomicity Levels and Requirements for Automated Machine Learning", Proceedings of the International Conference on Research in Adaptive and Convergent Systems, pp. 46-48, 2017, Sept.

Gupta, K., & Jiwani, N. (2021). A systematic Overview of Fundamentals and Methods of Business Intelligence. International Journal of Sustainable Development in Computing Science, 3(3), 31-46.

Tomar, U., Chakroborty, N., Sharma, H., & Whig, P. (2021). AI based Smart Agricuture System. Transactions on Latest Trends in Artificial Intelligence, 2(2).

WHIG, P. (2021). Innovative Smart Blind Guidance System Based on IoT. Transactions on Latest Trends in IoT, 3(3).

WHIG, P. (2019). Application of Machine learning to investigate the mortality risk of viral diseases. Transactions on Latest Trends in IoT, 1(1).

Kolla, Venkata Ravi Kiran, A Comparative Analysis of OS Forensics Tools (April 2, 2022). International Journal of Research in IT and Management (IJRIM), Vol. 12 Issue 4, April- 2022 , Available at SSRN: https://ssrn.com/abstract=4413730

Kolla, Venkata Ravi Kiran, Emojify: A Deep Learning Approach for Custom Emoji Creation and Recognition (January 11, 2021). International Journal of Creative Research Thoughts, 2021, Available at SSRN: https://ssrn.com/abstract=4413719

Kolla, Venkata Ravi Kiran, Heart Disease Diagnosis Using Machine Learning Techniques In Python: A Comparative Study of Classification Algorithms For Predictive Modeling (September 6, 2015). International Journal of Electronics and Communication Engineering & Technology, 2015, Available at SSRN: https://ssrn.com/abstract=4413723

Kolla, Venkata Ravi Kiran, A Secure Artificial Intelligence Agriculture Monitoring System (July 31, 2021). JounalNX, 2021, Available at SSRN: https://ssrn.com/abstract=4413466

Kolla, Venkata Ravi Kiran, Paws And Reflect: A Comparative Study of Deep Learning Techniques For Cat Vs Dog Image Classification (December 20, 2020). International Journal of Computer Engineering and Technology, 2020, Available at SSRN: https://ssrn.com/abstract=4413724

Kolla, Venkata Ravi Kiran, Forecasting the Future of Crypto currency: A Machine Learning Approach for Price Prediction (December 1, 2020). International Research Journal of Mathematics, Engineering and IT, Volume 7, Issue 12, December 2020, Available at SSRN: https://ssrn.com/abstract=4413732

Kolla, Venkata Ravi Kiran, Forecasting the Future: A Deep Learning Approach for Accurate Weather Prediction (December 01, 2018). International Journal in IT & Engineering (IJITE), 2018, Available at SSRN: https://ssrn.com/abstract=4413727

Kolla, Venkata Ravi Kiran, Forecasting Laptop Prices: A Comparative Study of Machine Learning Algorithms for Predictive Modeling (December 30, 2016). International Journal of Information Technology & Management Information System, 2016, Available at SSRN: https://ssrn.com/abstract=4413726

Kolla, Venkata Ravi Kiran, Analyzing the Pulse of Twitter: Sentiment Analysis using Natural Language Processing Techniques (August 1, 2016). International Journal of Creative Research Thoughts, 2016, Available at SSRN: https://ssrn.com/abstract=4413716

Meenigea , N., & kolla, V. ravi kiran. (2013). Heart Disease Prediction using Deep Learning and Artificial intelligence. International Journal of Statistical Computation and Simulation, 5(1). Retrieved from https://journals.threws.com/index.php/IJSCS/article/view/150

Meenigea, N. (2014). Type 2 Diabetes mellitus treatment intensification and deintensification. Transaction on Recent Devlopment in Industrial IoT, 6 (6).

Meenigea, N. (2022). Evaluation of antioxidant potential and antimicrobial activity. Transactions on Latest Trends in Health Sector, 14(14). Retrieved from https://ijsdcs.com/index.php/TLHS/article/view/269

Meenigea, N. (2022). In hospital deprescribing in the real world. Transactions on Latest Trends in Artificial Intelligence, 3(3). Retrieved from https://ijsdcs.com/index.php/TLAI/article/view/276

Meenigea, N. (2019). A systematic review OF splitting a tablet obtain an accurate dose. International Journal of Machine Learning for Sustainable Development, 1(2), 51-60. Retrieved from https://www.ijsdcs.com/index.php/IJMLSD/article/view/273

Meenigea, N. (2019). EMOJIFY-CREATE YOUR OWN EMOJIS WITH DEEP LEARNING. International Journal of Sustainable Development in Computing Science, 1(1), 31-39.

Meenigea, N. (2015). Assessing the acceptance of augmented-reality. Transaction on Recent Devlopment in Artificial Intellgence and Machine Learning, 7 (7).

Meenigea, N. kolla, V. ravi kiran.(2019). Classification of Fruits/Vegetables using TensorFlow. International Transactions in Artificial Intelligence, 3(3).

Meenigea, N. kolla, V. ravi kiran.(2013). Heart Disease Prediction using Deep Learning and Artificial intelligence. International Journal of Statistical Computation and Simulation, 5(1).

Meenigea, N. (2021). Safety of metaraminol in critically ill patients with shock. International Journal of Sustainable Devlopment in Computer Science Engineering, 7(7).

Meenigea, N. (2021). Virtual Objective Structured Clinical Examinations. International Scientific Journal for Research, 3 (3).

Meenigea, N. (2020). Experiential-based foundational pharmacy residency programs: a narrative review. International Scientific Journal for Research, 2 (2).

Meenigea, N. (2020). Exploring career advancement of pharmacy. Transaction on Recent Devlopment in Artificial Intellgence and Machine Learning, 12 (12).

Meenigea, N. (2018). Building a pharmacy workforce from the ground up to support the COVID-19 vaccine rollout. Transactions on Latest Trends in IoT, 1(1), 61-67. Retrieved from https://www.ijsdcs.com/index.php/TLIoT/article/view/278

Meenigea, N. (2018). Knowledge and perceptions of outpatients regarding upper respiratory tract. International Journal of Managment Education for Sustainable Development, 1(1), 50-55.

Meenigea, N. (2018). A Comparative Analysis of OS Forensics Tools in Health Sector. Transaction on Recent Devlopment in Industrial IoT, 10 (10).

Meenigea, N. (2017). Developing a mobile device-based medicines management application for people who are blind and visually impaired. Transaction on Recent Devlopment in Artificial Intellgence and Machine Learning, 9 (9).

Meenigea, N. kolla, V. ravi kiran.(2017). DETERMINING TELECOM COMPANY CHURN PREDICTION USING MACHINE LEARNING. International Transactions in Artificial Intelligence, 1(1).

Meenigea, N. (2023). Exploring the Current Landscape of Artificial Intelligence in Healthcare. International Journal of Sustainable Development in Computing Science, 1(1). Retrieved from https://www.ijsdcs.com/index.php/ijsdcs/article/view/285

Meenigea , N., & kolla, V. ravi kiran. (2013). Heart Disease Prediction using Deep Learning and Artificial intelligence. International Journal of Statistical Computation and Simulation, 5(1). Retrieved from https://journals.threws.com/index.php/IJSCS/article/view/150


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