Lesson 5 Intrusion Detection Systems

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Lesson 5Intrusion Detection Systems
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Overview

• History
• Definitions
• Common Commercial IDS
• Specialized IDS

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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

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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.

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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

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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

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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 dont care who attacks my system as
  long as I can recognize that the attack is taking
  place and block it.

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History of ID

• 1980 - John Andersons Computer Security Threat
  Monitoring and Surveillance
• 1987 - Dorothy Denning An Intrusion Detection
  Model
• Laid groundwork for commercial products
• First IDS, circa 1993 USAF ASIM

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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
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Model Components

• 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

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Haystack
Canonical Audit trail
9-track Tape
Preprocessor
Statistical Analysis
Z-248 PC
Audit Data
Reports
Unisys 1100
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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
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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
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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.
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Distributed IDS (DIDS)
Unmonitored host
Monitored Host
Monitored Host
DIDS Director
Unmonitored host
LAN Monitor
Monitored Host
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Cooperating Security Monitors (CSM)
Command Monitor
User Interface
Other CSMs
Local IDS
CSM
Intruder Handler
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Current IDS Trends

• Immature
• Manpower intensive
• High false alarm rates
• Dynamic to the point of instability
• Quietly Evolving

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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

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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

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Intrusion Detection System--Network Based A
Layer in the Defense
Adversary
INTERNET
External ROUTER
FIREWALL
DMZ Server(s)
INTERNAL NETWORK
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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

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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

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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)?

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

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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

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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

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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 dont 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

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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-9219) 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.

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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

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Summary

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