Intrusion Detection

1
Intrusion Detection

• CSEM02
• University of Sunderland
• Harry R. Erwin, PhD

2
Resources

• B. Schneier, 2000, Secrets and Lies, Wiley, ISBN
  0-471-25311-1.
• E. Amoroso, 1999, Intrusion Detection,
  Intrusion.net, ISBN 0-9666700-7-8
• R. G. Bace, 2000, Intrusion Detection, Macmillan
  Technical Publishing, ISBN 1-57870-185-6
• We will mostly follow Schneier in this lecture.

3
Intrusion Detection Systems (IDS)

• Network Monitorswatch your network looking for
  suspicious behavior
• Often but not always based on Audit
• Provide reactive rather than proactive security
• Alert on successful and ongoing attacks
• Need to be accurate in detecting attacks and in
  determining that an attack is not underway.
• Also may provide diagnosis tools.

4
The False Alarm Problem

• Base rate fallacysuppose you have a test that is
  99 accurate. Is this good?
• Not necessarily!
• Suppose the real attack rate is 1x10-6. This test
  will generate 10,000 false positives for every
  real attack it detects. (Work it out)
• If network attacks are rare, a test has to be
  powerful to be useful.

5
The Timely Notification Problem

• You may want to be warned in time to do
  something, but
• What about slow attacks? When should the IDS
  become suspicious and tell you?
• What about ambiguous evidence? Do you want to be
  warned about borderline cases?

6
The Response Problem

• What do you do if you do hear an alarm? I.e., the
  problem with giving out general warnings of
  terrorist activity.
• Options include
• Wait
• Collect more information
• Do something
• Hope it goes away
• You may be too busy fighting alligators to do
  anything intelligent about draining the swamp.

7
Approaches to Building an IDS

• Misuse detection
• IDS knows what an attack looks like and looks for
  it.
• Network virus scanner
• Fast, easy to build, has a low false positive
  rate.
• Misses a lot and is easy to fool.
• Probably will get better over time.

8
Approaches to Building an IDS (II)

• Anomaly detection
• Generates a statistical or neural network model
  of the network to figure out what is normal
• Sounds an alarm for abnormal activity
• Uses AI
• Bayesian statistics
• Neural networks
• Expert systems

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Problems with Anomaly Detection

• Does the training data include an attack? Then
  hacking will be considered normal. 8(
• New things happen on networks all the time.
  Successful retraining of an existing AI system to
  handle this is a hard problem, worth a PhD. 8(
• How can it categorize attacks? That requires
  expert input. 8(
• False positives are much higher. 8(
• Attack indicators are brittle, so that hackers
  can sneak past them. 8(

10
Inline versus Audit-Based IDS

• Should the IDS detect attacks in real-time or
  using audit log processing?
• Inline will have incomplete data.
• Inline is also computationally expensive.
• Audit log processing is after the fact.
• Audit log formats vary quite a bit.
• A combined approach is feasible, but costly.

11
Host-Based versus Network-Based IDS

• Network-based IDS is basically wire-tapping
• Stealthy
• Operating-system independent
• Host-based IDS uses audit logs
• From workstations, servers, switches, routers,
  etc.
• Product-specific.

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Make or Buy

• Do your own monitoring or pay someone else?
• Counterpane
• Qinetiq
• Other vendors important, too.
• SRM is a local company that does this.
• Trust issues particularly important.
• Inhouse expertise requirement.

13
Honey Pots and Burglar Alarms

• Burglar alarms are resources on the network that
  generate an alarm if accessed incorrectly.
• Honey pots are burglar alarms dressed up to look
  attractive. May incorporate subnetworks and dummy
  computers.
• Costly
• Have to look real to the attackers
• Legality important. Entrapment may be an issue,
  so intruders must be warned.
• Read http//csrc.nist.gov/publications/secpubs/ber
  ferd.ps
• See also http//www.strategypage.com/fyeo/howtomak
  ewar/default.asp?targetHTIW.HTM

14
Incident Handling Issues

• Be prepared
• Have procedures
• Dont panic
• Call in the police?
• Expectation management
• Damage control
• Dealing with witch hunts

15
IDS Requirements

• Must be
• Effective
• Easy to use
• Adaptable
• Robust
• Fast
• Efficient
• Safe

16
Future IDS Needs

• Should be
• Accommodating
• Security enhancing
• Scalable
• Realistic
• Hardened

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Conclusions

• We arent there yet,
• But any IDS system is better than none at all.
• This is the place to be if you want to work on
  secure systems development.