Real-Time Threat Detection with JavaScript: Monitoring and Response Mechanisms |
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© 2023 by IJCTT Journal | ||
Volume-71 Issue-11 |
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Year of Publication : 2023 | ||
Authors : Vishal Patel | ||
DOI : 10.14445/22312803/IJCTT-V71I11P105 |
How to Cite?
Vishal Patel, "Real-Time Threat Detection with JavaScript: Monitoring and Response Mechanisms," International Journal of Computer Trends and Technology, vol. 71, no. 11, pp. 31-39, 2023. Crossref, https://doi.org/10.14445/22312803/IJCTT-V71I11P105
Abstract
Web apps are essential to contemporary life but are also vulnerable to many security concerns. This article examines real-time threat detection, monitoring, and response techniques at the confluence of JavaScript and security. This study improves online application security by using JavaScript's unique characteristics. This paper examines real-time threat detection methods and their application in JavaScript-driven systems. We demonstrate safe JavaScript development and real-time threat detection and response. We show how these methods protect web applications in real-world cases.
This paper aims to:
● Explore JavaScript for real-time threat detection.
● Give practical advice on JavaScript monitoring and logging.
● Display real-time threat mitigation techniques.
The methodology begins with a comprehensive literature study on real-time threat detection and online application security. Code examples and case studies demonstrate how the topics are used. This research provides a comprehensive understanding of real-time threat detection with JavaScript, equipping developers and security practitioners to protect web applications from evolving threats.
Keywords
Real-time threat detection, JavaScript, Web security, Monitoring, Response mechanisms.
Reference
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[Google Scholar] [Publisher Link]
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[33] Karen Scarfone, and Peter Mell, “Guide to Intrusion Detection and Prevention Systems (IDPS),” National Institute of Standards and Technology (NIST), pp. 1-127, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[34] J. Mena et al., “A Survey of Big Data Architectures and Machine Learning Algorithms in Large-Scale Data Predictive Analytics,” Journal of King Saud University - Computer and Information Sciences, 2015.
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[CrossRef] [Google Scholar] [Publisher Link]
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[CrossRef] [Google Scholar] [Publisher Link]
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[39] M. Johnson, and R. Adams, “Web Application Security: Current Challenges and Future Directions,” Security Trends, vol. 26, no. 1, pp. 33-48, 2019.
[40] S. Robinson, “Enhancing Web Application Security: Current Challenges and Future Directions,” Security Trends, vol. 22, no. 4, pp. 113- 128, 2020.
[41] Jeremy Straub, “Modeling Attack, Defense and Threat Trees and the Cyber Kill Chain, ATT&CK and stride Frameworks as Blackboard Architecture Networks,” 2020 IEEE International Conference on Smart Cloud (SmartCloud), pp. 148-153, 2020.
[CrossRef] [Google Scholar] [Publisher Link]