Page 1441 - (ISC)² CISSP Certified Information Systems Security Professional Official Study Guide

If the hurricane has winds in excess of 120 miles per hour (mph),
then wood-frame structures will be destroyed.

If it is late in the hurricane season, then hurricanes tend to get

stronger as they approach the coast.

In an actual expert system, the knowledge base would contain
hundreds or thousands of assertions such as those just listed.

The second major component of an expert system—the inference
engine—analyzes information in the knowledge base to arrive at the
appropriate decision. The expert system user employs some sort of

user interface to provide the inference engine with details about the
current situation, and the inference engine uses a combination of
logical reasoning and fuzzy logic techniques to draw a conclusion
based on past experience. Continuing with the hurricane example, a
user might inform the expert system that a Category 4 hurricane is
approaching the coast with wind speeds averaging 140 mph. The
inference engine would then analyze information in the knowledge

base and make an evacuation recommendation based on that past
knowledge.

Expert systems are not infallible—they’re only as good as the data in
the knowledge base and the decision-making algorithms implemented
in the inference engine. However, they have one major advantage in
stressful situations—their decisions do not involve judgment clouded
by emotion. Expert systems can play an important role in analyzing

emergency events, stock trading, and other scenarios in which
emotional investment sometimes gets in the way of a logical decision.
For this reason, many lending institutions now use expert systems to
make credit decisions instead of relying on loan officers who might say
to themselves, “Well, Jim hasn’t paid his bills on time, but he seems
like a perfectly nice guy.”

Machine Learning

Machine learning techniques use analytic capabilities to develop
knowledge from datasets without the direct application of human
insight. The core approach of machine learning is to allow the
computer to analyze and learn directly from data, developing and