Table of Contents
What is a Security Information and Event Management Platform (SIEM)?
A Security Information and Event Management (SIEM) system is a comprehensive solution that aggregates and analyzes log and event data from various sources within an organization’s infrastructure, including servers, network devices, and applications.
By centralizing this data, SIEMs provide real-time analysis of security alerts generated by these hardware and software entities. Their primary purposes are to provide a unified view of an organization’s security posture, detect anomalous activities, facilitate incident response, and ensure compliance with industry regulations.
SIEM platforms can identify patterns and detect abnormal activities suggesting a security threat. SIEM solutions are particularly effective at identifying coordinated attacks, ongoing attacks across the network, and patterns that could indicate a potential future attack.
Examples of SIEMs are:
- Splunk
- URL: https://www.splunk.com/
- Description: Offers powerful data search capabilities, monitoring, and analytics, with SIEM functionality through its Enterprise Security app.
- LogRhythm
- URL: https://www.logrhythm.com/
- Description: Provides an integrated SIEM platform with log management, network monitoring, and advanced security analytics.
- IBM QRadar
- URL: https://www.ibm.com/qradar
- Description: Consolidates log events and network flow data from various sources, offering advanced threat detection and incident response features.
- ArcSight (from Micro Focus)
- URL: https://www.microfocus.com/en-us/cyberres/secops/arcsight-esm
- Description: Offers real-time threat detection, with a unique capability to process vast amounts of data, ideal for large enterprises.
- SolarWinds Security Event Manager
- URL: https://www.solarwinds.com/security-event-manager
- Description: It offers an easy-to-use interface and visualizations, making it suitable for businesses of various sizes.
How Does a SIEM Process Threat Data?
A SIEM processes threat data by collecting and aggregating log and event information from various sources within an organization’s infrastructure. Once gathered, advanced algorithms and predefined correlation rules are applied to the data to identify abnormal patterns or suspicious activities. By cross-referencing this data against known threat signatures and behavioural baselines, the SIEM can detect potential security incidents in real time. When anomalies are detected, the SIEM generates alerts, enabling cybersecurityCybersecurity refers to the practice of protecting computers, servers, mobile devices, electronic systems, networks, and data from digital attacks, damage, or unauthorized access. It encompasses techniques to prevent cyber threats... teams to take timely action, investigate the issue, and mitigate potential threats.
Here’s a simplified outline of the process:
- Data Collection: SIEM platforms gather event data from across the organization’s digital infrastructure, including network devices, systems, and applications.
- Normalization: The SIEM software normalizes the data, transforming it into a standard format for easier comparison and correlation. This process allows the system to analyze data from diverse sources.
- Aggregation and Correlation: The platform aggregates the data and looks for correlations that might indicate a coordinated attack or other security threat.
- Threat Identification: The SIEM system identifies potential threats using predefined rules and patterns. These rules can be as simple as repeated failed login attempts or as complex as sophisticated attack patterns.
- Alerting: When the SIEM system identifies a potential issue, it alerts the organization’s security personnel to the threat. Depending on the platform and its configuration, this alert might include recommendations for responding to the threat.
With the help of this expert-led book, you’ll become well-versed with SOAR, acquire new skills, and make your organization’s security posture more robust. You’ll learn how SOAR works and its benefits, including optimized threat intelligenceThreat intelligence in cybersecurity refers to organized, analyzed, and refined information about potential or current attacks on an organization. It provides insights into the tactics, techniques, and procedures (TTPs) used..., incident response, and utilizing threat hunting in investigations. You’ll also get to grips with advanced automated scenarios and explore useful tools such as Microsoft Sentinel, Splunk SOAR, and Google Chronicle SOAR.
Role of Artificial Intelligence in SIEM Platforms
Artificial intelligence (AI) has become a key element in advanced SIEM systems. AI can greatly enhance a SIEM platform’s ability to process large volumes of data and detect threats more effectively and efficiently.
AI technologies like machine learning are used to create models of normal activity based on the log data the SIEM system collects. The system can then compare new data against these models to detect abnormal activities suggesting a security threat.
For instance, Splunk Enterprise Security employs AI and machine learning algorithms to identify behaviour anomalies and sophisticated threats, greatly enhancing its detection capabilities.
AI can also help reduce the number of false positives, as it can learn from past data and security personnel feedback which threats are genuine and which are not. By automating this process, AI can save time and resources and enable security teams to focus on genuine threats.
Furthermore, AI can identify patterns and correlations that human analysts or simple rule-based systems might miss. For example, it can spot a series of minor events happening in different parts of the network that, taken individually, might not raise a flag but, when viewed as a whole, indicate a coordinated attack.
In conclusion, SIEM platforms, particularly those enhanced with AI, are crucial in today’s cybersecurity landscape. Collecting, processing, and analyzing threat data in real-time, these systems play a vital role in detecting, preventing, and responding to security threats.
