Security information and event management (SIEM) platforms combine SIM and SEM, aggregating both historical log data and real-time events and establishing relationships that can help security staff identify anomalies, vulnerabilities and incidents.
- Security information management (SIM): A first-generation, built on top of traditional log collection and management systems. SIM introduced long-term storage, analysis, and reporting on log data, and combined logs with threat intelligence.
- Security Event Management (SEM): A second-generation, addressing security events – aggregation, correlation and notification for events from security systems such as antivirus, firewalls and intrusion detection systems (IDS), as well as events reported directly by authentication, SNMP traps, servers, databases and others.
The main focus of SIEM is on security-related incidents and events, such as succeeded or failed logins, malware activities or escalation of privileges. These insights can be sent as notifications or alerts, or discovered by security analysts using the SIEM platform’s visualization and dashboarding tools.
Analyzes events and sends out alerts to notify security staff of immediate issues, either by email, other types of messaging, or via security dashboards.
Creates visualizations to allow staff to review event data, see patterns and identify activity that does not conform to standard patterns.
Automates the gathering of compliance data, producing reports that adapt to security, sgovernance and auditing processes for standards like HIPAA, PCI/DSS, HITECH, SOX and GDPR.
Stores long-term historical data to enable analysis, tracking, and data for compliance requirements. Especially important in forensic investigations, which happen after the fact.
Allows security staff to run queries on SIEM data, filter and pivot the data, to proactively uncover threats or vulnerabilities.
Provides case management, collaboration and knowledge sharing around security incidents, allowing security teams to quickly synchronize on the essential data and respond to a threat.
Integrates with other security solutions using APIs, and lets security staff define automated playbooks and workflows that should be executed in response to specific incidents.
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 ever more organizational sources, and using AI techniques to understand what type of behavior constitutes a security incident.
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.
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 low cost. This makes it possible to retain and analyze 100% of log data across even more platforms and systems.
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.
The central purpose of a SIEM is to pull together all the data and allow 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.
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 IDS with information from an antivirus product. 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.
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.
SIEMs can help security analysts determine that a security incident is taking place, triage the event and define immediate steps for 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 discover 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.
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.
Security information and event management tools provide:
* Real-time visibility across an organization’s information security systems.
* Event log management consolidates data from numerous sources.
* A correlation of events gathered from different logs or security sources, using if-then rules that add intelligence to raw data.
* Automatic security event notifications. Most SIEM systems provide dashboards for security issues and other methods of direct notification.
Logichub can integrate with SIEM to send audit logs through the Syslog protocol, and create a complete audit picture of privileged account activities in the enterprise SIEM solution.
CRIBL platform (Stream & Edge) is used by the customer for collecting data from the collectors, applying parsing rules on top of them and then ingesting data to S3 or ElasticSearch/Kibana which can later be queried.
- CRIBL Stream route and transform logs and metrics, on your own infrastructure or cloud infrastructure.
- CRIBL Edge helps you collect and process observability data – logs, metrics, application data, etc. – in real-time, from your Linux machines, apps, microservices etc., and deliver them to Cribl Stream or any supported destination.
There are a number of security information and event management solutions on the market. ElasticSearch/Kibana is among the most popular
- Kibana enables you to give shape to your data and navigate the Elastic Stack. With Kibana, you can:
* Search, observe, and protect your data. From discovering documents to analyzing logs to finding security vulnerabilities, Kibana is your portal for accessing these capabilities and more.
* Analyze your data. Search for hidden insights, visualize what you’ve found in charts, gauges, maps, graphs, and more, and combine them in a dashboard.
* Manage, monitor, and secure the Elastic Stack. Manage your data, monitor the health of your Elastic Stack cluster, and control which users have access to which features.
Updated about 1 month ago