DISCUSSION [NIST SP 800-171 R2]

Correlating audit record review, analysis, and reporting processes helps to ensure that they do not operate independently, but rather collectively. Regarding the assessment of a given organizational system, the requirement is agnostic as to whether this correlation is applied at the system level or at the organization level across all systems.

Further Discussion

Companies must review, analyze, and report audit records to help detect and respond to security incidents in a timely manner for the purpose of investigation and corrective actions. Collection of audit logs into one or more central repositories may facilitate correlated review. Small companies may be able to accomplish this manually with well-defined and -managed procedures. Larger companies will use an automated system for analysis that correlates log data from across the entire enterprise.Some companies may want to orchestrate the analysis process to include the use of Application Programming Interfaces (APIs) for collection, correlation, and the automation of responses based on programed rulesets.

Example

You are a member of a cyber defense team responsible for audit log analysis. You run an automated tool that analyzes all the audit logs across a Local Area Network (LAN) segment simultaneously looking for similar anomalies on separate systems at separate locations. After extracting anomalous information and performing a correlation analysis [b], you determine that four different systems have had their event log information cleared between 2:00 AM to 3:00 AM, although the associated dates are different. The team monitors all systems on the same LAN segment between 2:00 AM to 3:00 AM for the next 30 days.

Potential Considerations

Are mechanisms used across different repositories to integrate audit review, analysis, correlation, and reporting processes [b]?13

Copyright

Copyright 2020, 2021 Carnegie Mellon University and The Johns Hopkins University Applied Physics Laboratory LLC.

Copyright 2021 Futures, Inc.

This material is based upon work funded and supported by the Department of Defense under Contract No. FA8702-15-D-0002 with Carnegie Mellon University for the operation of the Software Engineering Institute, a federally funded research and development center, and under Contract No. HQ0034-13-D-0003 and Contract No. N00024-13-D-6400 with the Johns Hopkins University Applied Physics Laboratory LLC, a University Affiliated Research Center.

The view, opinions, and/or findings contained in this material are those of the author(s) and should not be construed as an official Government position, policy, or decision, unless designated by other documentation.

NO WARRANTY. THIS MATERIAL IS FURNISHED ON AN “AS-IS” BASIS. CARNEGIE MELLON UNIVERSITY AND THE JOHNS HOPKINS UNIVERSITY APPLIED PHYSICS LABORATORY LLC MAKE NO WARRANTIES OF ANY KIND, EITHER EXPRESSED OR IMPLIED, AS TO ANY MATTER INCLUDING, BUT NOT LIMITED TO, WARRANTY OF FITNESS FOR PURPOSE OR MERCHANTABILITY, EXCLUSIVITY, OR RESULTS OBTAINED FROM USE OF THE MATERIAL NOR ANY WARRANTY OF ANY KIND WITH RESPECT TO FREEDOM FROM PATENT, TRADEMARK, OR COPYRIGHT INFRINGEMENT.