SWARM INTELLIGENCE IN SAAS ECOSYSTEMS: MULTI-AGENT COORDINATION FOR THREAT NEUTRALIZATION

The rapid proliferation of SaaS applications within enterprise environments has created complex, interconnected ecosystems that present expanded attack surfaces for sophisticated cyberthreats.Traditional security methodologies encounter challenges when addressing the scale, dynamism, and distributed nature of these environments. This research introduces an innovative framework that applies swarm intelligence principles within multi-agent systems (MAS) to bolster security inSoftware as a Service (SaaS) ecosystem.By emulating the natural collective behavior of decentralized selforganizing systems, our approach empowers autonomous agents to collaboratively detect, analyze, and neutralize cyber threats without requiring centralized control.The findings indicate substantial enhancements in response time, threat coverage, and adaptive defense capabilities compared with conventional security models.This decentralized strategy effectively addresses critical SaaS security issues, including configuration drift, access management vulnerabilities, and evolving threat landscapes while delivering real-time protection across interconnected application environments.

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Publication Details

Journal
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY
Published
2025-05-15
DOI
https://doi.org/10.34218/ijcet_16_03_011
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
Field-Weighted Citation Impact
0.00
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article

SWARM INTELLIGENCE IN SAAS ECOSYSTEMS: MULTI-AGENT COORDINATION FOR THREAT NEUTRALIZATION

Pradipta Kishore Chakrabarty
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY
Evolutionary Game Theory and Cooperation
article

SWARM INTELLIGENCE IN SAAS ECOSYSTEMS: MULTI-AGENT COORDINATION FOR THREAT NEUTRALIZATION

Pradipta Kishore Chakrabarty
article en

Abstract

The rapid proliferation of SaaS applications within enterprise environments has created complex, interconnected ecosystems that present expanded attack surfaces for sophisticated cyberthreats.Traditional security methodologies encounter challenges when addressing the scale, dynamism, and distributed nature of these environments. This research introduces an innovative framework that applies swarm intelligence principles within multi-agent systems (MAS) to bolster security inSoftware as a Service (SaaS) ecosystem.By emulating the natural collective behavior of decentralized selforganizing systems, our approach empowers autonomous agents to collaboratively detect, analyze, and neutralize cyber threats without requiring centralized control.The findings indicate substantial enhancements in response time, threat coverage, and adaptive defense capabilities compared with conventional security models.This decentralized strategy effectively addresses critical SaaS security issues, including configuration drift, access management vulnerabilities, and evolving threat landscapes while delivering real-time protection across interconnected application environments.

INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGYVol. 16(3)
University of Richmond (US)
Openalex Percentile: Top 86%
Evolutionary Game Theory and Cooperation
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