An Explanation of Knowledge and Behavior-Based Detection Within an IDS

An Intrusion Detection System (IDS) is a type of security device that analyzes data packets and compares them against known signatures. The goal of an IDS is to detect intrusions before they cause damage. In this blog post we will explain how an IDS can identify harmful events using Knowledge-based detections and Behavior-based detections, along with the different aspects, benefits, and drawbacks.

What is knowledge-based detection?

Knowledge-based detection is also known as signature-based or pattern-matching detection. Essentially, the IDS searches a signature database schema for matches to all events. If the events align, the IDS concludes an attack is actually occurring. The suspect graph is constructed by the IDS provider after evaluating and reviewing several attacks on different systems. As a consequence, a definition, or signature, of known attack techniques is produced. An IDS, like many antivirus programs, utilizes knowledge-based identification features.


The fundamental disadvantage of a knowledge-based intrusion detection system is that it is only effective for recognized attack techniques. Recent tactics or different variants of previous attacks frequently go undetected by IDS.

Solution: Having the signature file up to date is critical to getting the most out of a knowledge-based IDS.

What is behavior-based detection?

The second category is behavior-based identification. A behavior-based intrusion detection system is also known as:

  • statistical intrusion detection,
  • abnormal activity detection,
  • and heuristics-based identification.

Essentially, behavior-based detection learns about your system’s usual behaviors and events by monitoring and analyzing them.

It can identify anomalous and potentially harmful actions and events once it has acquired sufficient information about routine activity. A behavior-based intrusion detection system is also known as a pseudo-artificial intelligence technology since it can understand and draw a conclusion about incidents. That is to say, the IDS may operate like a professional individual by comparing current incidents to previously recorded ones. The more data a behavior-based intrusion detection system receives about regular actions and incidents, the more reliable its abnormal activity diagnosis becomes.


The fundamental disadvantage of a behavior-based intrusion detection system is that it generates a large number of false alerts. The usual practice of user and system behavior might differ tremendously, making it hard to define usual or tolerable activity.

A behavior-based intrusion detection system (IDS) may identify unanticipated, new, and undiscovered weaknesses, attacks, and intrusion tactics by using known patterns, behavior records, and heuristic assessment of current and past events.

Similar aspects of knowledge-based and behavior-based detection

While knowledge-based and behavior-based detection approaches differ, they both use a detector system. An alarm is activated when an attack is identified or suspected.

This alarm system may warn admins by e-mail or notifications, as well as by running programs that transmit pager alerts. In addition to administrator warnings, an alarm system may record and monitor alert messages and create infringement records outlining identified attacks and vulnerability findings.


As we have learned, knowledge-based detection approaches utilize all known vulnerabilities of certain attacks, whereas behavior-based detection is familiar with usual communication and may detect malicious activities by studying differences from anticipated or regular activity. Each has different set of advantages and drawbacks which you now have a strong knowledge of upon completion of this blog.

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