Data Analytic for Cyber Security: A Review of Current Framework Solutions, Challenges and Trends

Abstract

In context of technology, cybersecurity has seen vital technological and operational developments in recent years, with information science at the forefront of the revolution. The key in creating a complicated and automatic security system is extracting network activity patterns or cybersecurity information insights and constructing an identical data-driven model. The applying of a spread of scientific methodology, machine learning techniques, processes, and systems; information science is to grasp and analyse actual occurrences with information. During this analysis, the researchers consider and in short justify cybersecurity information science, during which information is obtained from relevant cybersecurity sources as well as legislations and analytics are wont to supplement the most recent data-driven trends to supply more practical security solutions. The paradigm of cybersecurity information science, in distinction to standard cybersecurity computing techniques, permits for more practical and complex computing. Researchers check and highlight variety of connected analysis topics and future directions. Additionally, researchers propose a multi-layered framework for cybersecurity modelling. Overall the target is to target the connection of data-driven deciding framework model for safeguarding systems from cyber-attacks, instead of simply discussing cybersecurity information science and applicable approaches.

Keywords

• Cyber security
• cybercrime
• data analytic
• legislations

References

1. Khan, S., Olivia, T.S.L., Khan, N., Why, N.K. & Tan, S. W. (2022). Data analytic for cyber security: a review of current framework solutions, challenges and trends. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM), 18, 1-6.