December 13, 2022
You can’t have high-quality log management and analysis without high-quality data.
Security information and event management processes rely on detailed, accurate logs to detect suspicious activity and trigger alerts. The quality and accuracy of that data directly impact the value of the SIEM platform itself.
Feeding bad data into your SIEM can lead to unpredictable results.
It may fail to detect critical threats or miscategorize suspicious activity. It may even trigger time-consuming false positives – which is exactly the problem SIEM solutions are supposed to fix!
This underscores the importance of providing accurate, high-quality data to your SIEM. The better this data is, the more accurate its analysis will be.
Data Collection Demands a Risk Management Approach
Most SIEM vendors rely on a volume-based pricing model and by-the-byte billing. This model makes sense from the vendor’s perspective, but it forces security teams to pay large SIEM bills or accept the risk of security blind spots.
Accidentally failing to store the right data can mean losing critical insight into a vulnerable process. When implementing SIEM technology, choosing what to store is one of the most important decisions a security leader must make.
Optimizing data ingestion for an enterprise-level organization comes with additional obstacles. Not all data sources support SIEM data ingestion protocols. This data can only be retrieved through scheduled log collection jobs and queries. There is no guarantee that data collected this way is immediately usable in a SIEM context, so it must be normalized first.
Collecting data from these sources requires choosing how to collect and how to normalize the data for SIEM processes. Security leaders do not have unlimited resources, so they must carefully choose which data sources are worthwhile. There is an element of risk involved, and security leaders must manage it effectively.
The complexity of this process depends on your choice of SIEM. Working with reputable SIEM implementation experts can dramatically improve the outcome of optimizing data ingestion.
Proper Data Ingestion Formatting for USM Anywhere
Any data source that supports the syslog protocol can send its logs directly to the USM Anywhere Sensor. This is also true for Graylog data stored in the GELF format. USM Anywhere also collects and queries log data from Amazon Web Services and Microsoft Azure, although some configuration is required.
The USM Anywhere platform can also collect and analyze endpoint event logs using the AlienVault agent. It supports host-based log collection, which requires manual installation and configuration. Data collection from some third-party apps and services can be automated using the AlienApps API.
In each case, USM Anywhere needs incoming data to be correctly formatted and organized. Improper formatting can generate conflicts in the way USM Anywhere parses event information.
Exabeam Data Lake Simplifies Data Ingestion
Exabeam Data Lake disrupts the traditional approach to log management and allows users to collect and store unlimited amounts of security data. Instead of binding customers to a volume-based pricing package, Exabeam Data Lake works on a user-based pricing model. This provides security teams with a scalable solution for collecting and analyzing security data from across the entire organization.
The solution can parse logs from hundreds of popular security technologies with no additional configuration. It comes with pre-built data visualization tools that let security teams address common compliance requirements. Exabeam Data Lake is built on ElasticSearch, a reputable open-source technology with proven scalability.
This makes the process of collecting and parsing log data much easier for security teams. There is no need to leave important data sources out due to resource constraints. However, proper configuration is still vital. Exabeam still needs accurate, timely data that precisely reflects real-world activity as it occurs.
Examine the Quality of your Data Before SIEM Implementation
The best time to audit data quality is before you start using it for security information and event management processes. The more you know about your data prior to implementation, the better your chances for successful deployment are.
SIEM implementation experts can provide key insight into the accuracy, completeness, consistency, integrity, and timeliness of the data you plan to use in your SIEM. Understanding how well your data sources meet these requirements is key to optimizing data ingestion for your SIEM. Whether you opt for volume-based pricing or not, this step is critical to the success of your SIEM implementation efforts.
Contact Castra for greater insight into proper configurations for your organization.