In highly networked modern world, conventional techniques of network security such as user authentication, cryptography and intrusion prevention techniques like firewalls are not enough, owing to formulations of new attacks. Intrusion detection systems are becoming an important need for today’s networks. Anomaly detection is used as a part of intrusion detection systems, which in turn use certain data mining techniques. Data mining techniques can be applied to the network data to detect possible intrusions. The foremost step in application of data mining techniques is the selection of appropriate features from the data.An intrusion is someone attempting to break into or misuse the system. An intrusion detection system (IDS) for short, attempts to detect an intruder breaking into the system or a legitimate user misusing system resources. The IDS will run constantly on the system, working away in the background, and only notifying the user when it detects something it considers suspicious or illegal. Whether the user appreciates that notification depends on how well the users have configured the intrusion detection system.
Note that there are types of potential intruders:
Outside Intruders: Most people perceive the outside world to be the largest threat to their security. The media scare over “hacker’ coming in over the Internet has only heightened this perception.
Inside Intruders: FBI studies have revealed that 80% of intrusions and attacks come from within organizations.
Book: Intrusion Detection by Rebecca Gurley Bace
Web resources: Guide to Intrusion Detection and Prevention Systems (IDPS)
The Role of Intrusion Detection Systems
Power Point Presentation (PPT): Intrusion Detection & Network Forensics
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