Machine Learning Techniques for Advanced Persistent Threat (APT)  Detection

Manoj Suresh Dhappadhule ,Suraj Shankarrao Damre

Machine Learning Techniques for Advanced Persistent Threat (APT) Detection

Authors

Manoj Suresh Dhappadhule ,Suraj Shankarrao Damre

Keywords:

Advanced Persistent Threat, Machine Learning, Intrusion Detection, Deep Neural Network, Random Forest, Cybersecurity

Abstract

Advanced Persistent Threats, usually called APTs, are among the most worrying problems incybersecurity today. Unlike normal malware that spreads quickly and gets noticed, APTs workquietly, often for months, before doing real damage. Traditional security tools like signature based antivirus and rule-based firewalls usually fail to catch them because

References

: Mayank Atreya, Navin Chhibber, Harvendra Singh, Explainable Machine Learning For Dynamic Pricing In Fast-Changing Retail Environments, 2022/4/9, Journal ,Available at SSRN 6011354, https://scholar.google.com/citations?view_op=view_citation&hl=en&user=fyViF1UAAAAJ&citation_for_view=fyViF1UAAAAJ:LkGwnXOMwfcC.

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Published

2024-05-20

How to Cite

Manoj Suresh Dhappadhule ,Suraj Shankarrao Damre. (2024). Machine Learning Techniques for Advanced Persistent Threat (APT) Detection . Journal of Computational Analysis and Applications (JoCAAA), 33(05), 3751–3763. Retrieved from https://www.eudoxuspress.com/index.php/pub/article/view/5646