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Because
of the increasing dependence which companies and government agencies
have on their computer networks the importance of protecting these
systems from attack is critical. A single intrusion of a computer
network can result in the loss or unauthorized utilization or modification
of large amounts of data and cause users to question the reliability
of all of the information on the network. There are numerous methods
of responding to a network intrusion, but they all require the accurate
and timely identification of the attack.
Intrusion Detection
Systems
The timely and
accurate detection of computer and network system intrusions has
always been an elusive goal for system administrators and information
security researchers. The individual creativity of attackers, the
wide range of computer hardware and operating systems, and the ever
changing nature of the overall threat to target systems have contributed
to the difficulty in effectively identifying intrusions. While the
complexities of host computers already made intrusion detection
a difficult endeavor, the increasing prevalence of distributed network-based
systems and insecure networks such as the Internet has greatly increased
the need for intrusion detection.
There are two
general categories of attacks which intrusion detection technologies
attempt to identify - anomaly detection and misuse detection .Anomaly
detection identifies activities that vary from established patterns
for users, or groups of users. Anomaly detection typically involves
the creation of knowledge bases that contain the profiles of the
monitored activities.
The second general
approach to intrusion detection is misuse detection. This technique
involves the comparison of a user's activities with the known behaviors
of attackers attempting to penetrate a system. While anomaly detection
typically utilizes threshold monitoring to indicate when a certain
established metric has been reached, misuse detection techniques
frequently utilize a rule-based approach. When applied to misuse
detection, the rules become scenarios for network attacks. The intrusion
detection mechanism identifies a potential attack if a user's activities
are found to be consistent with the established rules. The use of
comprehensive rules is critical in the application of expert systems
for intrusion detection.
Current approaches
to intrusion detection systems
Most current
approaches to the process of detecting intrusions utilize some form
of rule-based analysis. Rule-Based analysis relies on sets of predefined
rules that are provided by an administrator, automatically created
by the system, or both. Expert systems are the most common form
of rule-based intrusion detection approaches. The early intrusion
detection research efforts realized the inefficiency of any approach
that required a manual review of a system audit trail. While the
information necessary to identify attacks was believed to be present
within the voluminous audit data, an effective review of the material
required the use of an automated system.
The use of expert
system techniques in intrusion detection mechanisms was a significant
milestone in the development of effective and practical detection-based
information security systems.
An expert system
consists of a set of rules that encode the knowledge of a human
"expert". These rules are used by the system to make conclusions
about the security-related data from the intrusion detection system.
Expert systems permit the incorporation of an extensive amount of
human experience into a computer application that then utilizes
that knowledge to identify activities that match the defined characteristics
of misuse and attack.
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