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Research PaperResearchia:202606.29014

GTI-mSEMP Framework : A Proposed Framework to Stimulate Malware Propagation with Inclusion of Attacker-Defender Strategy

Shadeeb Hossain

Abstract

The rapid proliferation of automated, multi-vector malware threats poses a significant risk to heterogeneous, resource constrained cyber-physical networks. Conventional epidemiological models often treat security defenses as static parameters, failing to capture the strategic, asymmetric maneuvers between an attacker and a defender. To address the gap, this paper proposes a Game-Theory-Integrated Modified Multi- Wireless Sensor Epidemic Malware Propagation (GTI-mSEMP) framework. This paper analy...

Submitted: June 29, 2026Subjects: Cybersecurity; Computer Science

Description / Details

The rapid proliferation of automated, multi-vector malware threats poses a significant risk to heterogeneous, resource constrained cyber-physical networks. Conventional epidemiological models often treat security defenses as static parameters, failing to capture the strategic, asymmetric maneuvers between an attacker and a defender. To address the gap, this paper proposes a Game-Theory-Integrated Modified Multi- Wireless Sensor Epidemic Malware Propagation (GTI-mSEMP) framework. This paper analyzed and compared the operational trajectories of Susceptible (S) and Recovered (R) node populations across three different operational regimes: Balanced Matchup, Exploit Surge and Hardened Defense. Numerical simulation results capture the real-time transient dynamics of the network state variables, demonstrating how the epidemic curve shifts when either the defensive or offensive scaling vectors hold an efficiency advantage. The proposed mathematical and numerical framework provides a rigorous foundation that can be deployed in highly adversarial network environments to evaluate dynamic malware propagation and predict localized node population states.


Source: arXiv:2606.28079v1 - http://arxiv.org/abs/2606.28079v1 PDF: https://arxiv.org/pdf/2606.28079v1 Original Link: http://arxiv.org/abs/2606.28079v1

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Submission Info
Date:
Jun 29, 2026
Topic:
Computer Science
Area:
Cybersecurity
Comments:
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