Logs are generated by network devices, software applications, operating systems, internet of things
devices and many other system hardware. They contain many information that are stored sequentially on
disk, files, or applications such as the Log Collector. Log is very important for any system because they
tell you what is happening and what your system is doing. Most of the processes running on your
system create logs. The problem is that these files often appear in different systems and in different
formats, and log data must be built in centralized and meaningful ways so that they are understandable
to humans and can be easily deciphered by machine learning systems. Log data collected from different
sources can be more easily related to relevant trends and patterns. Analysts should ensure that the log
data contains all necessary information and this information is explained by context, for example, one
system can use "alerts", the other uses "significant". Analysis are simplified and error free by ensuring
that word and data formats are synchronized. Log elements need to be generalized, using similar words
Log Analysis Key to Cyber Threat Detection 5
or terminology to avoid confusion and provide harmony, while generalization analyst should ensure that
statistics data reports from different sources are accurate and make sense to the reader.
Logs should also be accessed from a central location, and log aggregation is a good way to get all these
logs in one place. For example, if you have different types of hosts, you can host different types of hosts
in different places. Ends with the log. If you have an error and need to point to your log, you should look
for dozens or hundreds of files to see what went wrong. Even with good tools, you can spend a lot of
time doing this and this can frustrate even the toughest system administrators. As soon as logs are
aggregated, cleaned and normalized, anomalies, such as network breaches patterns can be identify
through thorough analysis