IDS Solutions in IoT Environments
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1 min read
Abstract
An evaluation of the architectural differences within IDS solutions, as well as a review of how these differences impact system reliability, computational efficiency and scalability.
- Context: IoT devices expand attack surfaces and strain traditional IDS because of limited CPU, memory, and heterogeneous protocols.
- Architectures examined:
- Hierarchical IDS: Modular but scales linearly; vulnerable to single‑point failures.
- Collaborative hierarchical (CSM): Peer‑to‑peer resilience; high bandwidth use and false‑positives.
- Mobile‑Agent Platforms: Local processing cuts traffic; consumes more energy and needs secure agents.
- Cluster‑Based: Local aggregation yields good scalability; cluster‑head can become a bottleneck.
- Hybrid: Combines strengths of multiple models; offers flexible scaling but adds orchestration overhead.
- Key finding: No single design fits all IoT contexts; choice depends on network topology, bandwidth, and security goals.
- AI/ML role: Federated learning boosts detection accuracy while preserving scalability, yet introduces adversarial‑model risks.
- Takeaway: Effective IoT IDS requires matching architectural trade‑offs to the specific environment and may benefit from adaptive, context‑aware orchestration.