With threats becoming more sophisticated, cybersecurity teams need tools that help them reduce risk. SIEM solutions combine security information and event management with threat monitoring, incident detection, and response.
They start by aggregating data from multiple collection agents and centralized servers. They then perform normalization and parsing for uniformity before performing event correlation using predefined rulesets or machine learning algorithms.
Real-time Alerts
SIEM tools offer real-time alerts based on event activity that could indicate the presence of a threat. These alerts help the security operations center (SOC) team prioritize threat activity and mitigate cyberattacks quickly to avoid costly financial implications and legal liability resulting from data breaches.
To provide accurate alerts, the best SIEM tools include a variety of functionalities. For example, they can perform a variety of data analytics to sort threat activities by patterns and identify abnormal behavior, as well as provide advanced features like user and entity behavioral analytics (UEBA) that illuminate deviations from standard user data patterns.
Other functions include log management, which collects data from various devices and systems across the network and centrally stores it for long-term analysis and reporting. It also provides real-time monitoring of events and alerts on system activity, identifying suspicious activities. It can also correlate this data to help the SOC team better understand what is happening on their network and take proactive action.
When selecting a SIEM solution, consider the organization’s priorities and requirements (specifically related to compliance), budget and level of IT expertise, and availability to assess and handle threats. To make the most of your investment, choose a solution that includes the capabilities you need and can add functionality as required.
Detection & Prevention
With an effective SIEM solution, you can identify a security threat in its early stages and take steps to reduce the damage caused. The software gathers events and logs data from host systems across the infrastructure, including antivirus filters and firewalls. It then identifies and categorizes the data so the organization can see potential threats or other problems at a glance on a centralized dashboard.
When a threat is detected, the software alerts IT professionals, who can quickly investigate and respond. The tool can also automate responses to shut down suspicious activities, such as blocking IP addresses, changing account privileges, or disabling devices. It can also create compliance reports that help companies demonstrate they comply with regulations, including HIPAA, PCI DSS, ISO, FERPA, FISMA, GLBA, and NERC CIP.
The best SIEM tools include advanced features designed to make it easier to improve security oversight and protect the network from attacks. These include advanced analytics with machine learning to identify anomalies, such as failed login attempts that aren’t typical for an individual user or a specific device. This cuts down processing requirements and the time needed to examine the activity. Other capabilities include threat intelligence to add context to incidents and identify known malicious actors in your environment; protocol intelligence to analyze captured packet data, such as DNS traffic and email activity; and user and entity behavior analysis (UEBA) that focuses investigations on accounts and devices with suspicious activities.
Reporting & Analysis
Reporting and analysis help you prioritize security alerts based on threat type, impact, and business risk. They also give you visibility into all activities on your IT system, so you can spot vulnerabilities and act fast. For example, user monitoring analyzes access and authentication data to identify suspicious behavior like failed login attempts or violations of corporate and regulatory policies. It can detect privileged user activity and establish user context to notify appropriate personnel.
Some SIEM tools also offer lateral movement detection by analyzing events, credentials, and systems to detect platform attack patterns. Others use entity behavioral analytics to detect anomalies in critical assets such as servers, medical equipment, and other devices with unique behaviors under normal conditions. And some have automated incident response to execute a pre-planned sequence of actions to contain an attack and mitigate the threat.
When choosing a SIEM tool for your organization, do your research. Ensure the tool meets your requirements and offers all necessary functionality. Look for a robust, reliable platform with centralized data management that eliminates blindspots for complete visibility. For instance, a SIEM solution should offer pre-processing to reduce the volume of data that needs to be stored on hard drives and in the cloud. In addition, it should use modern data lake technology to support unlimited scalability at a low cost.
Automation
SIEM tools aim to streamline security teams’ triage, validation, and response processes. This enables them to focus more on high-priority threats and helps to reduce the time it takes for organizations to identify and respond to breaches.
A centralized view of your network infrastructure is essential to catching security incidents before they harm you. The best SIEM solutions offer data aggregation to gather event information from multiple systems, networks, and devices. Then, a powerful SIEM tool uses correlation to find similar attributes and alert you when something unusual occurs.
For example, some of the top SIEM platforms use anomaly-based threat-hunting strategies to detect and mitigate malware. This type of detection does not rely on a database of known attack signatures to catch manual intrusion and zero-day attacks.
Moreover, next-gen SIEM solutions also incorporate machine learning to help detect incidents without pre-existing rules or attack signatures. These events can include unauthorized access, lateral movement, and covert communications.
The best SIEM tools also provide contextual information on users, assets, and networks to improve detection capabilities further. This includes user behavior analysis (UBA) that analyzes activities associated with specific people or devices to identify potential threats; protocol intelligence to locate and interpret captured packet data; and web intelligence for deeper insights into suspicious activity.