SIEM Explained: Security Information and Event Management

Security Information and Event Management (SIEM) is a category of security software that ingests log and event data from across an organisation's IT environment, normalises it into a common schema, and then applies correlation rules, statistical models, and threat intelligence feeds to detect suspicious activity. The term was coined by Gartner in 2005 by combining two older disciplines — Security Information Management (SIM), which focused on long-term log storage and compliance reporting, and Security Event Management (SEM), which focused on real-time event monitoring and alerting. Modern SIEM platforms merge both functions and increasingly add User and Entity Behaviour Analytics (UEBA) and Security Orchestration, Automation and Response (SOAR) capabilities as well.

For Australian businesses subject to the Security of Critical Infrastructure Act (SOCI), the Australian Signals Directorate's Essential Eight, or industry-specific frameworks such as PCI DSS or APRA CPS 234, a SIEM is often the cornerstone technology that enables compliance. It provides the audit trail needed to demonstrate that security events are being captured, reviewed, and acted upon in a timely manner. Without a SIEM, security teams are left manually sifting through individual device logs — an approach that simply does not scale.

A SIEM platform operates through a multi-stage pipeline. The first stage is data collection, where agents, syslog forwarders, API connectors, and native integrations pull log data from firewalls, switches, servers, endpoints, cloud platforms, SaaS applications, and identity providers. Common transport methods include syslog over TLS, Windows Event Forwarding (WEF), and REST API polling. The second stage is parsing and normalisation, where raw log entries — which arrive in dozens of different vendor-specific formats — are mapped to a common data model so that a firewall deny event from Fortinet and a block event from Palo Alto can be queried with the same field names.

The third stage is correlation and detection. This is where the SIEM adds real value. Correlation rules look for patterns across multiple data sources that might indicate an attack — for example, a VPN login from an unusual country followed by a privilege escalation event on a domain controller within five minutes. Rules can be simple threshold triggers (more than ten failed logins in sixty seconds) or complex chains. Modern SIEMs supplement rule-based detection with machine learning models that baseline normal behaviour and flag anomalies, reducing reliance on predefined signatures.

The final stages are alerting and response. When a correlation rule fires, the SIEM generates an alert that is routed to the Security Operations Centre (SOC) for triage. Depending on severity and confidence, the alert may trigger an automated playbook — for instance, disabling a compromised user account via API call to Azure AD — or it may be queued for manual investigation. The SIEM also retains indexed log data for forensic search, allowing analysts to pivot from an alert into the raw events that triggered it and explore adjacent activity.

The most common SIEM use cases span threat detection, compliance, and operational intelligence. On the threat detection front, organisations use SIEM to identify brute-force attacks, lateral movement, data exfiltration, malware command-and-control callbacks, insider threats, and account compromise. Correlation rules map to the MITRE ATT&CK framework, giving analysts a shared language to describe the tactics and techniques they observe. For compliance, the SIEM generates scheduled reports that prove log retention policies are being met, privileged account activity is audited, and security incidents are investigated within mandated timeframes.

Operationally, SIEM data feeds dashboards that track metrics such as mean time to detect (MTTD) and mean time to respond (MTTR), giving management visibility into the effectiveness of their security program. Some organisations also use the SIEM for IT operations monitoring — tracking authentication failures to detect misconfigured service accounts, spotting DNS anomalies that indicate infrastructure problems, or correlating application errors with network events to accelerate root-cause analysis.

Splunk Enterprise Security is widely regarded as the most mature SIEM on the market. Its Search Processing Language (SPL) is exceptionally powerful for ad hoc investigations, and its ecosystem of apps and add-ons supports hundreds of data sources out of the box. The trade-off is cost — Splunk's per-GB pricing can escalate quickly as log volumes grow, making capacity planning a critical discipline. Microsoft Sentinel, by contrast, is a cloud-native SIEM built on Azure Log Analytics with deep integration into the Microsoft 365 ecosystem — Defender for Endpoint, Azure AD Identity Protection, and Intune all feed data into Sentinel with minimal configuration. Its KQL (Kusto Query Language) is straightforward to learn, and built-in playbooks powered by Azure Logic Apps allow automation without a separate SOAR purchase. For Australian organisations already invested in Microsoft licensing, Sentinel often delivers the fastest time to value.

Wazuh is an open-source SIEM and XDR platform that has gained significant traction among managed service providers in Australia. Because it is free to deploy, resellers can offer SIEM-as-a-service without the per-GB licensing overhead of commercial platforms, passing savings on to their SMB clients. Wazuh includes host-based intrusion detection, file integrity monitoring, vulnerability detection, and compliance dashboards out of the box. The platform stores data in an Elasticsearch-compatible indexer, giving teams access to familiar query and visualisation tools.

A SIEM without skilled analysts watching it is little more than an expensive log archive. The platform must be embedded within a Security Operations Centre (SOC) workflow to deliver value. In a typical SOC, Tier 1 analysts monitor the SIEM alert queue, performing initial triage — confirming whether an alert represents a true positive, a benign true positive (real activity that is expected), or a false positive. Tier 2 analysts handle escalated incidents, conducting deeper investigation using the SIEM's search and correlation capabilities. Tier 3 analysts or threat hunters proactively query the SIEM for indicators of compromise not covered by existing detection rules.

For resellers offering managed security services, the SIEM is the operational backbone. Multi-tenancy support becomes essential — the ability to ingest, segregate, and report on data from dozens or hundreds of client environments within a single platform. Both Splunk and Wazuh support multi-tenancy natively, while Sentinel achieves it through Azure Lighthouse cross-tenant management. Defining clear escalation procedures, SLA-driven alert prioritisation, and automated enrichment (e.g., looking up IP reputation or querying threat intelligence APIs when an alert fires) are all critical to running an efficient SOC.

SIEM costs are driven primarily by data ingestion volume and retention duration. A mid-size organisation with 500 endpoints, several firewalls, and a handful of servers can easily generate 20-50 GB of logs per day. At Splunk's list pricing, that volume can run into tens of thousands of dollars per year; with Sentinel, costs depend on the Log Analytics workspace pricing tier and commitment reservations. Effective cost management requires log source prioritisation — not every log is equally valuable for security. DNS query logs, for instance, are high-volume but essential for detecting command-and-control traffic, whereas verbose application debug logs may be better left out of the SIEM entirely.

Strategies for controlling cost include tiered storage (hot for recent data, warm or cold for older logs), filtering noisy but low-value events at the collection layer, and using summary indexes or data transforms to reduce the volume of retained raw data. Australian data sovereignty requirements should also factor into architecture decisions — ensure that log data stays within Australian regions if regulated, which is straightforward with Azure's Australia East and Australia Southeast regions for Sentinel, or on-premises deployment for Splunk and Wazuh.

Many Australian SMBs lack the budget and expertise to run a SIEM in-house, yet they face growing regulatory pressure to demonstrate security monitoring. This gap creates a compelling opportunity for IT resellers to offer SIEM-as-a-Service — deploying, managing, and monitoring a SIEM on behalf of clients. Using an open-source platform like Wazuh, resellers can keep licensing costs near zero while charging a monthly per-endpoint or per-seat fee for management and monitoring. Layering in 24/7 SOC coverage through a partner MSSP adds further value and recurring revenue.