IIARD International Institute of Academic Research and Development

INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND MATHEMATICAL THEORY (IJCSMT )

E-ISSN 2545-5699
P-ISSN 2695-1924
VOL. 11 NO. 1 2025
DOI: 10.56201/ijcsmt.v11.no1.2025.pg97.114

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Leveraging Application Programming Interface (API) Call Patterns for Real-Time Dynamic Malware Detection Using Deep Learning

V C Uzodinma, N D Nwiabu, E O Taylor

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Abstract

With the rise in new malware threats in recent years, where data security and response time are crucial for both businesses and home users, the threat is expected to worsen. Despite the widespread use of anti-malware software, malware infections continue to grow rapidly. These attacks are often aimed at stealing credentials, executing unauthorized commands, or installing additional malware. One concerning method is dynamic malware attacks through API calls, where malicious code interacts with an application's APIs in real-time. The attacker exploits vulnerabilities in the application or its infrastructure to access sensitive data or take control of the system. To address the issue of dynamic malware attacks through API calls, this paper introduces a technique for detecting and classifying such attacks.

keywords:

API Call Pattern, Real-Time, Malware

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