A Beginner’s Guide to Intrusion Detection Systems

As industrial and enterprise networks grow in complexity-spanning cloud services, OT/ICS systems, IIoT endpoints and remote access-the challenge of detecting unauthorised activity has never been greater. While firewalls, segmentation and endpoint controls form the backbone of defence, they alone cannot guarantee visibility into what’s happening inside the network. That’s where a robust Intrusion Detection System (IDS) comes in.

In this beginner’s guide for CyberSec Magazine, we’ll unpack what an IDS is, why it matters-especially in the OT/ICS and IoT space-explain the types of IDS solutions, walk you through deployment considerations, highlight emerging trends for 2025, and point you to best practices so your organisation can achieve real detection & response visibility.

1. Background: Why IDS Matter More Now Than Ever

1.1 The evolving threat landscape for IT + OT
The digital transformation of industrial operations has caused formerly isolated Operational Technology (OT) networks to become interconnected with enterprise IT, vendor access, cloud services and IIoT devices. This convergence increases the attack surface and weakens traditional perimeter‑only defences. According to industry commentary, OT/ICS environments often lack the contextual visibility found in IT networks.
Meanwhile the global market for Intrusion Detection and Prevention Systems (IDPS) is projected to grow from roughly USD 7.09 billion in 2025 to USD 20.18 billion by 2034, implying greater investment and expectation in this space.

1.2 From prevention to detection
Firewalls, antivirus, access controls-they handle many threats. But sophisticated adversaries, insider threats, lateral movement, zero‑day exploits and stealthy intrusion campaigns all require detection capability. An IDS serves as a second line of defence: it monitors, alerts, and provides visibility into anomalous, suspicious or policy‑violating activity that may bypass other controls.
For industrial/OT contexts, detection is particularly critical because safety, reliability and availability depend on early recognition of faults or intrusions-and downtime costs can be very high.

2. What is an Intrusion Detection System (IDS)?

An IDS is a technology and set of processes that monitor network traffic, system logs or device behaviour, identify patterns indicative of malicious or suspicious activity, and raise alerts to security or operations‑teams for investigation.
It is not a prevention system by default-though many modern systems blur the line by incorporating preventive actions (thus often called IDPS).
Key functions of an IDS include:

• Traffic/behaviour monitoring and analysis
• Signature‑based detection of known threats
• Anomaly‑based detection of deviations from a baseline
• Alert generation (and sometimes automated response)
• Integration with Security Information and Event Management (SIEM), logs and orchestration

3. Types of IDS and How They Differ

For those new to the topic, it helps to classify IDS solutions across several dimensions:

3.1 By deployment location

• Network‑based IDS (NIDS): Monitors traffic on network segments (e.g., between IT and OT zones, across vendor access links).
• Host‑based IDS (HIDS): Runs on endpoints or servers and monitors system calls, file integrity, logs, internal host behaviour.

3.2 By detection method

• Signature‑based IDS (SIDS): Uses known attack patterns/signatures to detect threats. Effective for known threats, less so for new ones.
• Anomaly‑based IDS (AIDS): Establishes a baseline of “normal” behaviour (network flows, device behaviour, protocols) and detects deviations. Particularly relevant where zero‑day or unknown threats are concerned.

3.3 By environment

• Industrial/OT‑specific IDS: Tailored for ICS/SCADA/IIoT networks: supports industrial protocols (Modbus, DNP3, OPC UA), passive monitoring (because active scanning may disrupt operations), integration with OT asset inventories and process context.
• Cloud/Virtual IDS: Deployed in virtualised or cloud environments monitoring east‑west traffic, containerised workloads, hybrid IT/OT traffic.

4. Why IDS in OT/ICS & Industrial Networks Should Be Different

Industrial networks have unique characteristics that affect how intrusion detection should be approached.

4.1 Legacy systems and constrained devices
Many ICS devices were designed without modern security in mind. They may have proprietary protocols, minimal logging, limited compute for security agents and cannot tolerate heavy scanning. As a result, monitoring approaches must be passive, non‑disruptive and tailored.
4.2 Real‑time, safety and availability constraints
In OT/ICS environments, downtime means production loss, safety incidents or regulatory impacts. An IDS must not generate disruptive false positives or scanning activity that could interfere with operations.
4.3 Convergence of IT and OT traffic – more lateral movement
Threats often begin in IT networks (e.g., a phishing breach) and then move laterally into OT. Many OT networks today lack visibility or monitoring of east‑west traffic (inside OT zone) or vendor remote sessions. An effective IDS in this environment must monitor device‑to‑device or zone‑to‑zone traffic.
4.4 Process‑ and protocol‑specific behaviour
Unlike data‑centric IT networks, OT traffic often involves process variables, control commands, timing patterns, PLC interactions. IDS tailored for these behaviours can detect abnormal process behaviour, not just network anomalies. Some recent research focuses on autoencoder‑based models for IIoT intrusion detection.

5. Key Features to Look for in an IDS in 2025

For enterprises and industrial operators selecting or evaluating an IDS today, these capabilities are increasingly important:

• Passive asset discovery & profiling – Particularly for OT, discovering devices and mapping behaviour without active scanning is vital.
• Protocol awareness – Ability to decode ICS/SCADA protocols (Modbus, DNP3, EtherNet/IP, OPC UA) and identify suspicious commands, unauthorised devices or unexpected traffic.
• Behaviour analytics & anomaly detection – Using machine learning/AI to detect abnormal activity patterns rather than relying solely on legacy signatures.
• Integration with security orchestration & SIEM – The IDS must feed into broader detection/response architecture: alerts should align with SOC workflows, asset context and incident response plans.
• Edge and IIoT support – Lightweight agents or remote sensors for edge/IIoT sites where connectivity may be limited, plus remote site monitoring.
• Low false positive rates & high availability – A system generating too many false alerts will be ignored, and if it disrupts operations it will be rejected by operations teams.
• Vendor access monitoring and segmentation support – Given the increasing role of third‑party/vendor access in incidents, an IDS should monitor remote/vendor sessions, jump hosts and segmentation boundaries.
• Scalable deployment across hybrid environments – On‑prem, cloud, multi‑site, remote / unmanned sites.
• Actionable intelligence and response support – Beyond alerting, the system should provide context (device, asset criticality, zone), support workflows, ideally enable automated or semi‑automated response.

6. Deployment Roadmap: How to Introduce an IDS in Your Environment

Here’s a practical deployment roadmap that organisations-especially those in industrial/OT settings-can follow.

Step 1: Prepare by mapping your assets and network topology
Start with foundational tasks: inventory of assets (IT + OT + IIoT), network diagrams showing IT‑OT boundaries, vendor access points and remote connections. This foundational visibility will inform where to deploy your IDS sensors.
Step 2: Define the zones and critical assets you want to monitor
Segment your environment logically (IT zone, OT zone, remote vendor zone, IIoT/edge zone). Identify which assets/processes are most critical (safety, production, regulatory).
Step 3: Choose sensor placement carefully
For network IDS: deploy sensors at boundaries (IT‑OT firewall, remote vendor access point) and inside zones for lateral movement visibility. For host‑based IDS: on critical engineering workstations or servers.
Step 4: Baseline behaviour and tune detection
Allow the system to observe normal traffic/behaviour for a period of time. Configure rules or models accordingly. For anomaly detection: train on baseline behaviour.
Step 5: Integrate with SOC/ops workflows
Define alert‑handling procedures: who receives, how escalation works, how investigations happen. Ensure alerts include context (asset, zone, risk level).
Step 6: Continuous review and tuning
Monitor false positive/false negative rates, refine detection models, update signatures, adjust sensors as network evolves (e.g., new IIoT devices, new remote access).
Step 7: Incident response readiness and playbooks
Link detection to response. If an alert triggers an intrusion scenario, have playbooks: isolate asset, vendor access revocation, forensic capture, recovery plan.
Step 8: Measure success and report metrics
Define KPIs: number of meaningful alerts, mean time to detection, mean time to response, reduction in unmanaged devices, compliance targets. Use these to justify investment and drive continuous improvement.

7. Emerging Trends & What to Expect in 2025 & Beyond

AI/ML‑enhanced IDS – Recent research highlights the use of autoencoders, deep learning, collaborative IDS architectures to reduce false positives and adapt to novel threats.
Edge/IIoT‑specific IDS – Lightweight IDS models deployed at the edge for IIoT networks, enabling detection close to devices where connectivity may be intermittent.
Hybrid IT/OT visibility and detection – As IT and OT converge further, IDS tools are evolving to span both domains, detect lateral movement across IT‑OT boundary and support IT‑OT teams.
Behavior‑based detection for process anomalies – In industrial systems, it’s not only network anomalies but process‑control anomalies (e.g., abrupt set‑point changes) that matter. IDS solutions are incorporating process data.
Collaborative/Distributed IDS frameworks – Systems that pool data from multiple sensors, sites and feed into centralised analytics to detect distributed threats or APT‑style campaigns.
Cloud and container traffic monitoring – With industrial operations leveraging cloud, microservices and remote workloads, IDS tools must support virtualised/cloud network flows.
Integration with Zero Trust and XDR architectures – IDS increasingly becomes one component in broader Extended Detection and Response (XDR) and Zero Trust frameworks, rather than a standalone point product.

8. Common Pitfalls & How to Avoid Them

Deploying an IDS isn’t without challenges. Here are pitfalls and how to mitigate them:

• High false‑positive volume → Tuning and baseline training must be adequate; work with operations to validate alerts.
• Insufficient asset visibility → You can’t detect what you don’t know exists. Start with asset inventory and passive discovery.
• Deploying active scanning in OT zones → Active scanning may disrupt OT devices; use passive sensors in OT/ICS environments.
• Siloed deployment (IT only) → Focusing only on IT networks leaves OT/IIoT gaps; include industrial zones.
• Over‑reliance on signature‑only detection → Signature‑based IDS won’t catch zero‑day or novel threats. Include anomaly‑based methods.
• Ignoring operational context (safety, availability) → In OT, detection systems must adhere to operational constraints.
• Lack of incident response integration → Alerts mean little if they don’t feed into response workflows.
• Not revisiting configuration as networks evolve → As new IIoT devices, vendor access paths and remote sites emerge, IDS configuration must evolve too.

9. Key Takeaways for Practitioners

• An IDS remains a critical component of a layered cybersecurity architecture-but it should be viewed as one tool among many.
• In industrial/OT environments, it must be tailored: passive monitoring, protocol awareness, process‑behaviour context and vendor access visibility are essential.
• Deploy with operational awareness: map assets, tune sensors, integrate with SOC and ensure response workflows.
• Aim for visibility, context and actionability-not simply generating alerts.
• Stay ahead of evolving threats: AI/ML, edge/IIoT, IT/OT convergence demand IDS capabilities to evolve.
• Treat deployment as a continuous improvement exercise, not a one‑time project. Measure performance, alert relevance and adjust.

Conclusion

For organisations managing industrial networks, IoT‑enabled systems or hybrid IT/OT environments, an Intrusion Detection System is no longer optional-it’s indispensable. But deploying just any IDS won’t guarantee security. The right approach combines asset visibility, behavioural detection, protocol awareness, and operational integration.

This guide has provided a structured overview: what IDS are, why they matter, how to select and deploy them, what to watch for in 2025, and common pitfalls to avoid. At CyberSec Magazine, our focus is on practical, actionable guidance that aligns cybersecurity with operations, safety and business goals. If you’re preparing to deploy or upgrade your IDS capability, consider asset discovery as your first step-and let detection become a strategic asset, not just another tool.

For further insights on OT/ICS and IoT‑security, and to explore solutions tailored for industrial environments, stay tuned and subscribe to our updates.