MULTI-AGENT INTRUSION DETECTION AND PREVENTION SYSTEMS (IDPS) IN CYBERSECURITY: ARCHITECTURES, BENCHMARKS, AND METHODOLOGICAL MITIGATION
Abstract
The exponential scaling and increasing heterogeneity of contemporary cloud infrastructures, Internet of Things (IoT) ecosystems, and distributed corporate networks have exposed severe architectural limitations in centralized Intrusion Detection and Prevention Systems (IDPS). Single-point bottlenecks, high alert triage latency, and systemic vulnerability to zero-day coordinated adversarial vectors necessitate a paradigm shift toward distributed computational defenses. Multi-Agent Intrusion Detection and Prevention Systems (MA-IDPS) present a modular framework where localized, specialized software entities autonomously sense, analyze, and collaboratively neutralize threat vectors across network perimeters. This article concludes with an analytical matrix juxtaposing current deployment strategies to furnish security architects with clear, resource-optimized guidelines for heterogeneous cloud infrastructures.