Multiagent Anti-Malware Model, a Paradigm Shift from Mere Detection to Prevention of Cyber Threats

• Author(s): Ibeneme-Sabinus, Ifeoma Livina; Agbakwuru Onyekachi Alphonsus; Eleberi Leticia Ebele
• Paper ID: 1712391
• Page: 2596-2600
• Published Date: 05-12-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 5 November-2025

Abstract

The security of information and data over the internet is one of the top challenges facing most business organization?s today as all businesses rely on internet services for their day-to-day operations. malware is one of the topmost challenging threats as systems are being locked up, business disrupted and even closed down as a result of this deadly threat. This research work deployed the activities of Mobile Agents. The agents were trained using Random Forest, Support Vector Machine and Decision Tree Machine Learning Algorithms to develop an Anti-Malware Model. In this research paper authentication scheme, the agents monitor all downloads including users? behaviour, scan all entries into the system, check for attachments in all external files and emails, eject external device, block all advertisements and flag up links and websites that are not registered into the Threat Intelligent Database (TID)as suspicious activities. With this the probability of success for all attempts to sneak into the system reaches near to zero. This practice will also solve the problem of False Positive Detection Rate (FPDR) during data training process as this model will serve as a mitigation apparatus to all kinds of malware activities as information are stored in the systems? Threats Intelligent Database (TID) for references and thereby cushion the effects and ugly activities of malware to our promising organizations.

Keywords

Mobile Agents, Anti-Malware, Machine Learning Algorithms, Threats Intelligent Database.

Citations

IRE Journals:
Ibeneme-Sabinus, Ifeoma Livina, Agbakwuru Onyekachi Alphonsus, Eleberi Leticia Ebele "Multiagent Anti-Malware Model, a Paradigm Shift from Mere Detection to Prevention of Cyber Threats" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 2596-2600

IEEE:
Ibeneme-Sabinus, Ifeoma Livina, Agbakwuru Onyekachi Alphonsus, Eleberi Leticia Ebele "Multiagent Anti-Malware Model, a Paradigm Shift from Mere Detection to Prevention of Cyber Threats" Iconic Research And Engineering Journals, 9(5)