What Is SIEM? Uses, Components, and Capabilities

What Is SIEM, Why Is It Important and How Does It Work?

Security information and event management (SIEM) solutions use rules and statistical correlations to turn log entries and events from security systems into actionable information. This information can help security teams detect threats in real time, manage incident response, perform forensic investigation on past security incidents, and prepare audits for compliance purposes.

Related content: This is part of an extensive series of guides about Network Security.

The term SIEM was coined by Mark Nicolett and Amrit Williams, in Gartner’s SIEM report, Improve IT Security with Vulnerability Management. They proposed a new security information system on the basis of two previous  technologies: Security Information Management (SIM) and Security Event Management (SEM).

Several years later, Gartner introduced a vision of a next-gen SIEM that goes beyond rules and correlations. Next-gen SIEM incorporates two key technologies: user and entity behavior analytics (UEBA) and security orchestration and automation response (SOAR). These technologies enable complex threat identification, detection of lateral movement, and automated incident response as an integral part of a SIEM’s functions.

Related content: Information Security

Why Is SIEM Important?

SIEM combines two functions: security information management and security event management. This combination provides real-time security monitoring, allowing teams to track and analyze events and maintain security data logs for auditing and compliance purposes.

SIEM offers a well-rounded security solution to help organizations identify potential and real security vulnerabilities and threats before they disrupt operations or cause lasting damage to their business reputation. SIEM makes behavioral anomalies visible to security teams, enhancing the monitoring process with AI to automate incident detection and response processes. It has replaced many manual tasks, becoming a ubiquitous tool for any security operation center (SOC).

In addition to providing log management capabilities, SIEM has evolved to offer various functions for managing security and compliance. These include user and entity behavior analytics (UEBA) and other AI-powered capabilities. SIEM provides a highly efficient system for orchestrating security data and managing fast-evolving threats, reporting requirements, and regulatory compliance.

How Does SIEM Work?

In the past, SIEMs required meticulous management at every stage of the data pipeline — data ingestion, policies, reviewing alerts, and analyzing anomalies. Increasingly, SIEMs are getting smarter at pulling data together, from more organizational sources, and using AI techniques to understand what type of behavior constitutes a security incident.

Data collection

Most SIEM systems collect data by deploying collection agents on end-user devices, servers, network equipment, or other security systems like firewalls and antivirus, or via protocols syslog forwarding, SNMP, or WMI. Advanced SIEMs can integrate with cloud services to obtain log data about cloud-deployed infrastructure or SaaS applications, and can easily ingest other non-standard data sources.

Pre-processing may happen at edge collectors, with only some of the events and event data passed to centralized storage.

Data storage

Traditionally, SIEMs relied on storage deployed in the data center, which made it difficult to store and manage large data volumes.

As a result, only some log data was retained. Next-generation SIEMs are built on top of modern data lake technology such as Amazon S3 or Hadoop, allowing nearly unlimited scalability of storage at a low cost. This makes it possible to retain and analyze 100% of log data across even more platforms and systems.

Policies and rules

The SIEM allows security staff to define profiles, specifying how enterprise systems behave under normal conditions.

They can then set rules and thresholds to define what type of anomaly is considered a security incident. Increasingly, SIEMs leverage machine learning and automated behavioral profiling to automatically detect anomalies, and dynamically define rules on the data, to discover security events that require investigation.

Data consolidation and correlation

The central purpose of a SIEM is to pull together all the data and allow the correlation of logs and events across all organizational systems.

An error message on a server can be correlated with a connection blocked on a firewall, and a wrong password attempted on an enterprise portal. Multiple data points are combined into meaningful security events, and delivered to analysts by notifications or dashboards. Next-gen SIEMs are getting better and better at learning what is a “real” security event that warrants attention.

SIEM Features and Capabilities

Analyzes events and helps escalate alerts to notify security staff of immediate issues, either by email, other types of messaging, or via security dashboards.

Dashboards and Visualizations
Creates visualizations to allow staff to review event data, see patterns, and identify activity that does not conform to standard processes or event flows.

Automates the gathering of compliance data, producing reports that adapt to security, governance and auditing processes for standards like HIPAA, PCI/DSS, HITECH, SOX, and GDPR.

Stores long-term historical data to enable analysis, tracking, and reporting for compliance requirements. Especially important in forensic investigations, which can occur long after the fact.

Threat Hunting
Allows security staff to run queries from multiple sources viaSIEM data, filter and pivot the data, and proactively uncover threats or vulnerabilities.

Incident Response
Provides case management, collaboration, and knowledge sharing around security incidents, allowing security teams to quickly synchronize on the essential data, communicate, and respond to a threat.

SOC AutomationIntegrates with other security solutions using APIs, and lets security staff define automated playbooks and workflows that should be executed in response to specific incidents.

Next-Gen SIEM Capabilities

SIEM is a mature technology and the next generation of SIEMs provide new capabilities:

  • User and entity behavior analytics (UEBA) in advanced SIEMs go beyond rules and correlations, leveraging AI and deep learning techniques to look at patterns of human behavior. This can help detect insider threats, targeted attacks, and fraud.
  • Security orchestration and automation response (SOAR) — Next-gen SIEMs integrate with enterprise systems and automate incident response. For example, the SIEM may detect an alert for ransomware and perform containment steps automatically on affected systems, before the attacker can encrypt the data, while simultaneously creating communications or other notifications.

New SIEM platforms provide additional advanced capabilities such as:

  • Complex threat identification — Correlation rules can’t capture many complex attacks, because they lack context, or can’t respond to new types of incidents. With automatic behavioral profiling, SIEMs can detect behavior that suggests a threat.
  • Detection without rules or signatures — Many threats facing your network can’t be captured with manually-defined rules or known attack signatures. SIEMs can use machine learning to detect incidents without pre-existing definitions.
  • Lateral movement — Attackers move through a network by using IP addresses, credentials, and machines, in search of key assets. By analyzing data from across the network and multiple system resources, SIEMs can detect this lateral movement.
  • Entity behavior analysis — Critical assets on the network such as servers, medical equipment or machinery have unique behavioral patterns. SIEMs can learn these patterns and automatically discover anomalies that suggest a threat.

Automated incident response — Once a SIEM detects a certain type of security event, it can execute a pre-planned sequence of actions to contain and mitigate the incident. SIEMs are becoming full security orchestration and automation response (SOAR) tools.

SIEM Use Cases

Security monitoring

SIEMs help with real-time monitoring of organizational systems for security incidents.

A SIEM provides a unique perspective on security incidents because it has access to multiple data sources — for example, it can combine alerts from an intrusion detection system (IDS) with information from an antivirus (AV)product and authentication logs. It helps security teams identify security incidents that no individual security tool can see, and helps them focus on alerts from security tools that have special significance.

Advanced threat detection

SIEMs can help detect, mitigate, and prevent advanced threats, including:

  • Malicious insiders — A SIEM can use browser forensics, network data, authentication, and other data to identify insiders planning or carrying out an attack.
  • Data exfiltration (sensitive data illicitly transferred outside the organization) — A SIEM can pick up data transfers that are abnormal in their size, frequency, or payload.
  • Outside entities, including advanced persistent threats (APTs) — A SIEM can detect early warning signals indicating that an outside entity is carrying out a focused attack or long-term campaign against the organization.

Forensics and incident response

SIEMs can help security analysts determine that a security incident is taking place, triage the event, and define immediate steps for escalation and remediation.

Even if an incident is known to security staff, it takes time to collect data to fully understand the attack and stop it — the SIEM can automatically collect this data and significantly reduce response time. When security staff discovers a historic breach or security incident that needs to be investigated, SIEMs provide rich forensic data to help uncover the kill chain, threat actors, and mitigation.

Compliance reporting and auditing

SIEMs can help organizations prove to auditors and regulators that they have the proper safeguards in place and that security incidents are known and contained.

Many early adopters of SIEMs used it for this purpose:  aggregating log data from across the organization and presenting it in audit-ready format. Modern SIEMs automatically provide the monitoring and reporting necessary to meet standards like HIPAA, PCI/DSS, SOX, FERPA, and HITECH.

The Future of SIEM

Companies usually will express two primary concerns regarding the ability of their existing technologies to handle cybersecurity threats now and in the future. First, SIEM solutions don’t usually support very large workloads (i.e., big data) and struggle to handle the large numbers of alerts and contextual data required. Second, most tools that detect, investigate, and respond to threats are unintuitive. 

These concerns are driving new solutions to address the needs of hybrid models, ever-growing data, digital transformations, and cloud-based environments. Modern practices often expose organizations to new threats, with attack surfaces growing alongside expanding systems. There is demand for new disruptive technology.

UEBA revolutionized the SIEM market back in 2013, reducing the risks resulting from the reliance of end-users on correlation rules. Later, innovations such as data lakes helped respond to cloud adoption trends by collecting logs from multiple cloud services. Next, SOAR capabilities and cloud-based SIEM accompanied further changes in market demand. 

Future cybersecurity tools will compete to provide data collection, processing, and storage capabilities at scale for ever-expanding cloud systems. Cloud-native offerings will provide several critical features via a fast, integrated, cloud-scale security platform. Additional capabilities of future SIEM solutions include limitless data transformation to ingest and process petabytes of data, an improved search experience to help find event data from massive logs via a unified interface, and an automated threat detection and incident response (TDIR) workflow. 

Automation will likely remain center-stage and expand to new areas, helping accelerate security incident investigation and response processes. Data-driven solutions will emphasize large-scale data analytics to support easy, reliable, and secure cloud systems. SecOps teams will leverage modern SIEM solutions to address challenges beyond the capabilities of existing tools. 

Future SIEM platforms will allow teams to automatically identify and respond to threats in real time, leverage pre-packaged cloud and security parsers, and process unlimited volumes of security data. They will provide high visibility, allowing teams to visualize and prioritize threats more effectively. 

This is the future we are creating — stay tuned for more on the next Exabeam disruption. 

Exabeam Fusion SIEM

Exabeam Fusion SIEM is a cloud-delivered solution that combines SIEM with the world-class threat detection, investigation, and response (TDIR) of Extended Detection and Response (XDR). 

With powerful behavioral analytics built into Fusion SIEM, analysts can detect threats missed by other tools. Prescriptive workflows and pre-packaged content enable successful SOC outcomes and response automation. Fusion SIEM also provides the cloud-based log storage, rapid and guided search, and comprehensive compliance reporting expected of any modern SIEM.

With Fusion SIEM you can:

  • Use threat detection events, investigation, and response from multiple tools
  • Collect, search, and enhance data from anywhere
  • Detect threats missed by other tools through behavioral analytics
  • Achieve successful outcomes with prescriptive, threat-centric use case packages
  • Enhance productivity and reduce response times with automation
  • Meet regulatory compliance and audit requirements with ease

How Exabeam Fusion Works

Data from anywhere enhances visibility  – Visibility is the first pillar of security operations, but it is a challenge to achieve as modern organizations are making data available everywhere. Inefficient and overly complex traditional logging tools often require knowledge of proprietary query language, and are slow to deliver results. The continuous spread of data, infrastructure, and applications requires a new level of analytics for full visibility. Fusion SIEM collects data from the endpoint to the cloud, eliminating blindspots to give analysts a full picture of their environment. Rapid, guided search boosts productivity, and ensures analysts of all levels can access valuable data exactly when they need it.

Prescriptive TDIR use case packages and automation – It has become too complicated to build an effective SOC using legacy SIEMs and a selection of purpose-built security products. Every SOC is unique, with its own mix of tools, level of staffing and maturity, and processes and there is no standard way to tackle cybersecurity. Fusion SIEM solves this by leveraging prescriptive, threat-centered TDIR Use Case Packages that provide repeatable workflows and prepackaged content that spans the entire TDIR lifecycle. These use cases include all the content necessary to operationalize that use case, including: prescribed data sources, parsers, detection rules and models, investigation and response checklists, and automated playbooks.

Meet regulatory compliance and audit requirements  – Organizations must adhere to compliance regulations. Creating and maintaining compliance reports is time consuming but necessary. Whether you’re subject to GDPR, PCI, HIPAA, NYDFS, NERC, or utilizing a framework such as NIST or directives from DISA or CISA, Fusion SIEM significantly reduces the operational overhead of compliance monitoring and reporting. Fusion SIEM’s pre-packaged reports provide huge time savings spent correlating information, solves the risk of missing vital data, and eliminates the need to manually create compliance reports through report builder tools.
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