Lesson 5 Intrusion Detection Systems

1. Lesson 5Intrusion Detection Systems

2. Overview • History • Definitions • Common Commercial IDS • Specialized IDS

3. Why Even Bother? • “One of the problems with anomaly detection is that even the current best research systems have something like a 75% success rate.” Marcus Ranum Network Flight Recorder

4. Intrusion Detection Defined • The process of monitoring the events occuring in a computer system or network and analyzing them for signs of intrusions, defined as attempts to compromise the confidentiality, integrity, availability, or to bypass the security mechanisms of a computer or network.

5. General Thoughts about ID • No Defense is Impenetrable • Vulnerabilities exist to bypass system security precautions • Automated tools exist to find and exploit vulnerabilities • A methodology to detect and report suspicious host and network activity must be implemented • IDS Goal: to characterize attack manifestations to positively identify all true attacks without falsely identifying non-attacks • ID is an instance of the general signal detection problem

6. Why use ID? • Increase the perceived risk of discovery and punishment • To detect attacks not prevented by other means • Detect and deal with probing • Document existing threats • QC for security design and admin • Forensics for improved security or prosecution

7. Goals of IDS • Accountability - “I can deal with security attacks that occur on my systems as long as I know who did it (and where to find them.)” • Response - “I don’t care who attacks my system as long as I can recognize that the attack is taking place and block it.”

8. History of ID • 1980 - John Anderson’s: Computer Security Threat Monitoring and Surveillance • 1987 - Dorothy Denning: An Intrusion Detection Model • Laid groundwork for commercial products • First IDS, circa 1993: USAF ASIM

9. Generic Intrusion Detection Model Activity Profile Design New Profiles Event Generator Update Profile State Create Anomaly Records Rule Set/ Detection Engine Define new & modify existing rules Audit trails, network packets application logs CLOCK

10. Rule Set - inference engine decides whether an intrusion has occurred or Generic detector examing events and state data using models, rules, patterns and statistics to flag intrusive behavior Activity Profile - Maintains state of system or network being monitored Feedback critical No architectural limitations Rule base can learn if programmed Model Components

11. Haystack Canonical Audit trail 9-track Tape Preprocessor Statistical Analysis Z-248 PC Audit Data Reports Unisys 1100

12. Intrusion Detection Expert System (IDES) Receiver Audit Records Audit Data Expert System Active Data Collector Active Data Anomaly Data Profile Updater Anomaly Detector Security Admin Interface Profile Data

13. Multics Intrusion Detection and Alerting System (MIDAS) Command Monitor Audit Records Preprocessor Network Interface Multics Fact Base Statistical Data Base System Security Monitor Rule Base Symbolics

14. Network Security Monitor (NSM) Network Traffic Packet Catcher Filter Object Detector & analyzer Report Generator Traffic Archive Network Profile – which systems normally connect to which others using what service. During a 2 month period, 110,000 connections analyzed at UC-Davis, NSM correctly identified over 300 intrusions, only 1% had been detected by admins.

15. Distributed IDS (DIDS) Unmonitored host Monitored Host Monitored Host DIDS Director Unmonitored host LAN Monitor Monitored Host

16. Cooperating Security Monitors (CSM) Command Monitor User Interface Other CSM’s Local IDS CSM Intruder Handler

17. Current IDS Trends • Immature • Manpower intensive • High false alarm rates • Dynamic to the point of instability • Quietly Evolving

18. Type of IDS • Signature based system • Attack description that can be matched to sense attack manifestations • Anomaly based detectors • equate “unusual” or “abnormal” as intrusions

19. IDS Classification Can base classification on what they sense • Network based systems (NIDS) • Sense packets on a network segment • Easy to deploy, but they suffer throughout problems • Host-based systems (HIDS) • Inspect audit or log data • Can affect performance on host • Hybrids • Combine the best of both

20. Intrusion Detection System--Network Based “A Layer in the Defense” Intrusion Detection System Other Network Defense Tools Adversary INTERNET External ROUTER FIREWALL DMZ Server(s) INTERNAL NETWORK

21. Network Based IDS • Some detect intrusions after the bad guy is inside….but at least you know • Others detect attacks (attack detect systems) • Location in architecture determines which one you have • Number of IDSes in architecture can add protetection • Balance comes between being inundated with false alarms or alert conditions requiring action • Ideal NIDs installation: start buy adding as few sensors as possible

22. Host based IDS • Setup a HIDs like a selective burglar alarm • Deploy HIDs on critical servers devoid of interactive users • Configuration optios • Critical file modification • When log files get smaller • Process table grows larger than normal or too fast

23. What the different levels of IDS do • Host-based Intrusion Detection • Will catch users logged directly into a system • Will miss network actions (the network as a whole) • Network-based Intrusion Detection • Will miss individual actions on the host the user is logged directly into. • Will be able to see attacks on multiple hosts (“door knob rattling”). • Where do you place the IDS? On the LAN or on the outside of the router (the connection to the Internet)?

24. Five Functional Areas of HIDS Log/Event Monitoring File Integrity Checking Policy Compliance Network Traffic Monitoring System Monitoring Ref: Rasmussen, ISSA, Mar 02

25. And what about IDS and the PSTN? • Two aspects • Detection of intrusions into the IP network from the PSTN • Detection of intrusions into the PSTN and its systems • Do you • Have a separate system, or • Feed current IDS with data from the PSTN?

26. Strengths of IDSes • Monitor and analysis of system events and user behaviors • Testing security states of system configurations • Recognizing known attack patterns • Recognizing anomalies • Measuring security policy enforcement • Managing Data Flow

27. Weaknesses of IDSes • Compensating for weak or missing security mechanisms • Instantaneous detection, reporting, and attack response • Detecting newly published attacks • Compensating for info source fidelity • Reducing manpower needs

28. IDS Adjusted Expectations • Consider a building with motion detectors • Works great when building is empty • But if activated during day many false positives • Building managers don’t expect them to work during the day • Its possible to set up network-based IDS (NIDS) and a host-based IDS (HIDS) to limit false positives

29. Monitoring and the Law • Issue is expectation of privacy – does the individual have one? • You generally need to inform individuals using the system that their actions are subject to monitoring. • Government systems have the warning banner. • This advice also issued by CERT (CA-92:19) for anybody wanting to monitor keystrokes. • Note that it is considered not enough to notify all authorized users (when they are issued their initial password for example), it must be displayed each time at login.

30. IDS Fad • “ People buy the hottest IDS tool that will be very good about telling them about DOS in the network, but is useless detecting problems inside the host.” • Matt Bishop, UC Davis

31. Summary • Detection of Incidents • Basic IDS Model-History • IDS Types and Classification