SIEM is now a $2 Billion industry, but only 21.9% of those companies are getting value from their SIEM, according to a recent survey.
SIEM tools are an important part of the data security ecosystem: they aggregate data from multiple systems and analyze that data to catch abnormal behavior or potential cyberattacks. SIEM tools provide a central place to collect events and alerts – but can be expensive, resource intensive, and customers report that it is often difficult to resolve problems with SIEM data.
Security Information and Event Management (SIEM) is a software solution that aggregates and analyzes activity from many different resources across your entire IT infrastructure.
SIEM collects security data from network devices, servers, domain controllers, and more. SIEM stores, normalizes, aggregates, and applies analytics to that data to discover trends, detect threats, and enable organizations to investigate any alerts.
How Does SIEM Work?
SIEM provides two primary capabilities to an Incident Response team:
Reporting and forensics about security incidents
Alerts based on analytics that match a certain rule set, indicating a security issue
At its core, SIEM is a data aggregator, search, and reporting system. SIEM gathers immense amounts of data from your entire networked environment, consolidates and makes that data human accessible. With the data categorized and laid out at your fingertips, you can research data security breaches with as much detail as needed.
identifies three critical capabilities for SIEM (threat detection, investigation and time to respond) — there are other features and functionality that you commonly see in the SIEM market, including:
Basic security monitoring
Advanced threat detection
Forensics & incident response
Log collection
Normalization
Notifications and alerts
Security incident detection
Threat response workflow
Top SIEM Tools
These are some of the top players in the SIEM space:
Splunk
Splunk is a full on-prem SIEM solution that Gartner rates as a leader in the space. Splunk supports security monitoring and can provide advanced threat detection capabilities.
IBM QRadar
QRadar is another popular SIEM that you can deploy as a hardware appliance, a virtual appliance, or a software appliance, depending on your organization’s needs and capacity.
LogRhythm
LogRhythm is a good SIEM for smaller organizations.
SIEM in the Enterprise
Some customers have found that they need to maintain two separate SIEM solutions to get the most value for each purpose since the SIEM can be incredibly noisy and resource intensive: they usually prefer one for data security and one for compliance.
Beyond SIEM’s primary use case of logging and log management, enterprises use their SIEM for other purposes. One alternate use case is to help demonstrate compliance for regulations like HIPAA, PCI, SOX, and GDPR.
SIEM tools also aggregate data you can use for capacity management projects. You can track bandwidth and data growth over time to plan for growth and budgeting purposes. In the capacity-planning world, data is key, and understanding your current usage and trends over time allows you to manage growth and avoid large capital expenditures as a reactionary measure versus prevention.
Limitations of SIEM Applications as a Full Data Security Ecosystem
SIEM applications provide limited contextual information about their native events, and SIEMs are known for their blind spot on unstructured data and emails. For example, you might see a rise in network activity from an IP address, but not the user that created that traffic or which files were accessed.
In this case, context can be everything.
What looks like a significant transfer of data could be completely benign and warranted behavior, or it could be a theft of petabytes of sensitive and critical data. A lack of context in security alerts leads to a ‘boy that cried wolf’ paradigm: eventually, your security will be desensitized to the alarm bells going off every time an event is triggered.
SIEM applications are unable to classify data as sensitive or non-sensitive and therefore are unable to distinguish between sanctioned file activity from suspicious activity that can be damaging to customer data, intellectual property, or company security.
Ultimately, SIEM applications are only as capable as the data they receive. Without additional context on that data, IT is often left chasing down false alarms or otherwise insignificant issues. Context is key in the data security world to know which battles to fight.
The biggest issue we hear from customers when they use SIEM is that it’s extremely difficult to diagnose and research security events. The volume of low-level data and the high number of alerts cause a ‘needle in a haystack’ effect: users get an alert but often lack the clarity and context to act on that alert immediately.
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