Network Security and Intrusion Detection

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Network SecurityandIntrusion Detection

• Survey of the Art and Practice
• Dr. Michah Lerner
• ATT Labs
• 15-August-2000

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Outline

• Model
• Principles
• Assumptions
• Methods
• Products

No silver bullets
Published sources only
Note this talk describes some attack models. If
youd like try them out, dont!
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Intrusion Detection Systems, IDS

• Identified by Dorothy Denning in 1987 IEEE
  Software Engineering
• Protect systems and networks from threats,
  vulnerabilities, and intrusions
• Art includes
• Bro A System for Detecting Network Intruders in
  Real Time (Vern Paxon)
• JiNao Protect link state routing Felix Wu
• Rule-based expert system, statistical analysis,
  protocol analysis, OSPF MIB, distributed
  programming interface (DPI)
• Vendors include
• Amazon.com lists 171 security products
• Axent (NetProwler, and Tivoli modules), ISS,
  Network Associates, Cisco

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A Story

• Jane the Dandelion wine merchant
• Running SSL to protect her eCommerce site
• Coalition against Dandelion Wine
• Quietly launches a chosen ciphertext attack
  against her SSL server (Daniel Bleichenbacher,
  LNCS 1462, 1998)
• Exploit weakness in SSL V.3.0
• Generate many authentication requests
• SSL reports which ones were incorrectly formatted

• The Coalition obtained her master secret!
• They tested about one million chosen
  ciphertexts on her server!
• She just thought that SSL was slow!
• IDS would have found incomplete SSL
  handshakes, and probably foiled the intruder

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Assumptions

• Assumptions
• RFC 1636 encryption essential to security
• Open networks violate this assumption
• Encryption should protect control information, as
  well as contents
• See section 7.3 of the RFC
• In attack from Vi ? net ? Vj assume only one of
  Vi, Vj is the attacker
• DDOS violates this assumption
• Assumptions are sometimes wrong
• Replay attack can masquerade with encrypted data
• Distributed attacks can leverage multiple
  attackers
• Encryption can be broken

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Concept Collection Analysis
CERN European Laboratory for Particle Physics
Birth Place of The Web Browser
http//www.cern.ch

• Every time something suspicious is detected, the
  sessions security weight is increased
• When the security weight gets higher than a
  given threshold, detailed monitoring starts
• Encryption was, until recently, not allowed by
  the French law

? Not much used for first break-in discovery, but
invaluable for security incident analysis and
follow-up it answers typical questions like
? When did the first break-in happen? ? Which
other systems may have been attacked? ?
Which other services on the attacked system
may have been compromised?
Security officer
Reports
Filter
Suspicious behavior
Network
Database
Analyzer
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Intrusion Examples

• Denial of Service
• Hijacking of session or router
• Theft
• Resources bandwidth theft or blockage
• Identity
• Information

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Intrusion at any layer or sliceDifficult and
Complex Problem
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Mobsters101 How to Intrude1

• Resources
• Exhaust, overload or consume
• Control Functions
• Undermine direct control protocols
• Assert authentication or authorization contrary
  to policy
• Block authentication or authorization
• Undermine indirect control
• Subvert timing or other policing methods
• Transport Functions
• Transmit forged content
• Modify, Read or Block content
• Many attackers use tools like COPS or SATAN,
  which automate the process of checking for known
  bugs in remote network systems. These freely
  available tools, as well as commercial tools such
  as ISSs Internet Scanner, are designed to help
  systems administrators audit their own networks,
  but are equally useful to an attacker.
  Wallach99
• See http//www.cert.org/advisories

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Intrusion Definition

• Intrusion
• Violation of the network policy, even where the
  policy is not completely stated
• Policy
• Allocation, usage and return of resources
• Possibly multiple policies active on a network
• Varied requirements of business, administration
  or trust
• Resources
• Finite
• Independent
• Layered
• Protocol-driven

• Protocols
• Efficient, not perfect
• IP spoofing packets are not uniquely
  att-ributable to the origin
• Costly to stop

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Prevention Policies Assurances

• Violations of policy may define intrusion
• Except
• Seldom have such a precise policy in IP
• The policy could be buggy
• New applications could violate the policy
• Cost is prohibitive for many applications
• Can plug anything into the Internet not just
  safe applications. IEEE 802.3 (Ethernet) is
  ubiquitous
• An alternative to formal policy is assurances
• General policy, but less rigorous
• Availability connections, bandwidth, low delay
• Integrity privacy, reliability, and low
  error-rate

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Detection

• Assurances are threatened by
• Misuse specific attack behavior
• Based on expert knowledge of patterns associated
  with attack
• Patterns of misuse defined by experts, or by
  machine learning should not occur
• Examples
• Mismatched SYN/ACK
• Same authenticated user from multiple locations?
• Multiple failed authentications? From different
  address??
• Problem only recognizes anticipated threats (but
  can combine several threats that might otherwise
  be missed)
• Anomalous use possible attack
• Recognize increased risk to network
• Compare actual with expected behavior
• Load rising atypically?

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How to Protect the Assurances?

• Redundancy
• Makes it harder to corrupt
• Make it easier to identify corruption
• May make it easier to locate the corruption
• Explicit redundancy add to network or data
• Tags and attributes
• Input/output validation
• Implicit redundancy already in the network
• Anonymous timing
• Private network attributes
• Content privacy and easily evaded
• Per-protocol or general properties
• State-machine compliance?
• Frame-format?

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Two Keys to Protection

• Prevention
• Define multiple layers
• Define behavior of each layer, including
  resources
• Enforce each behavior
• Prohibit actions that may compromise the behavior
• Examples
• IP DDOS does not affect ATM integrity
• Replay of short-lifetime HTTP cookies is
  traceable
• Link-layer marking
• Ingress/egress filtering
• End-to-end coordination

• Detection
• Identify correct behavior
• Reinforce or augment
• Redundancy
• Format (protocol)
• Augmentation (tags)
• Validations
• Characterize activities
• Recognize anomalies
• Unusual transit duration, route, or augmentation
• Item invalid packet header
• Aggregate bad path or invalid protocol sequence
• Honeypot traces

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Explicit Redundancy Protection

• Content transformation
• SSL
• Cookies
• Protocol hardening against adversarial errors
• IPSec
• Invalid session properties (i.e. stale keys,
  invalid context or content) may indicate attack
• Packet augmentation
• Security labels
• Properties inherited from ingress
• Requirements incumbent upon egress
• Min/max trust and validation of information flow1
• Management at Ingress/Egress
• Interaction with authentication and multiple
  domains

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Implicit Redundancy Detection

• Packet
• Well-formed packets (protocol-compliant)
• Well-defined packets (service behavior)
• Source, destination, format
• May validate endpoints and actions
• Traffic profile
• Acquire by observation of usage
• Statistical model distinctive characteristics
  (packet size, timing) not on connection
  contents
• Resists encryption, and preserves privacy
• Database of representative samples
• Does the traffic profile fit the
  source/destination profiles?

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General Technique

• Collect traffic and audit information
• Protocol analysis
• Various sensors
• Content-independent sensors may work even on
  encrypted data
• State-based sensors evaluate the trustworthiness
  of connection path
• State-free sensors operate without change to
  firewall or network-element
• Compute patterns of misuse or abuse
• Recognize patterns of a possible attack
• Previously observed or predicted attack patterns
• Uncharacteristic changes in predicted performance

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Information to Collect

• Audit information
• Management information bases (MIBS) and logs
• After-the-fact analysis of traffic artifacts
• Historical information
• Recognition of previously used contents, such as
  serial numbers, someone elses password, etc.
• Strength of evidence follows the strength of the
  content source
• Distributed
• Exchange data on suspected intrusions (IETF IDWG)
  
• Information from IP authentication systems

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Information to Compute

• Attack signatures
• Hard problem needs attack models to organize
  data
• Attacks are often distributed requires
  coordination
• ISS publishes about 350 Real Secure Signatures at
  http//www.iss.net
• Backdoors
• Denial of Service
• Distributed Denial of Service
• OS Sensor
• Suspicious Activity
• Unauthorized Access Attempts
• Only three detect RIP attacks on routing
• None of the published signatures mention
  streaming, VoIP, MPEG, Quality of Service, or
  attacks on OSPF

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Detailed Taxonomy

• Knowledge-based
• Expert systems Signature analysis
• Petri nets State-transition analysis
• Behavior-based
• Statistics Expert systems
• Neural networks User Intention model

Source IBM RZ 3176 ( 93222) 10/25/99 Computer
Science/Mathematics (23 pages). A ReviseTaxonomy
for Intrusion-Detection Systems by Hervé Debar,
Marc Dacier, Andreas Wespi
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Information Collection Tools

• Tcpdump
• Bro
• NetMon
• Snort
• All canuse rules

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Protocol Monitoring

• Validate Appropriate Traffic Flows
• Multiple granularities of description
• Recognize change from the behavior
• Activation/deactivation of connections
• Correlation/evaluation of connection attributes
• How
• Protocol scrubbing InfoComm 2000
• State machines for correct protocol flow
• Error states for erroneous traffic
• Pattern recognition
• Simulation/validation of expected behaviors
• Does the expected response follow, or something
  else?

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ASAX and Russel
(RUle-baSed Sequence Evaluation Language)

• State full event detection
• Correlation of events across multiple hosts
• consolidate intrusion evidence from several
  scattered sources and correlate them
  intelligently at a central location.

FW-1

• SYN-Flood
• IP spoof
• Port Scan
• Host Scan
• etc.

Router
FUNDPUniv.
Internet
ISP
Sniffer
ASAX
Source Aziz MounjiAbdelaziz.Mounji_at_swift.com
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Russell -- ASX
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What if Alert?

• Block offending traffic sources
• Terminate suspicious processes
• Coordinate with multiple domains
• Intruder Detection and Isolation Protocol (IDIP)
• Trace
• Report
• Directive (discovery coordinator)

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Products(Names changing all the time)

• Boundary controllers
• NAI Gauntlet, ARGuE, MPOG, etc.
• Secure Computing Sidewinder
• Detectors
• Axent, Cisco
• SRI Emerald expert-system
• NAI CyberCop
• ISS RealSecure
• NFR www.nfr.net
• Event-based traffic analysis, pattern matching,
  aggregation and adaptation
• SUNY, BRO, CIDF, IDIAN, DPF packet filter
  compiler

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Vendors and Products Tivoli Compatibility
Source RZ 3253 ( 93299) 06/26/00 Computer
Science 45 pages Integration of Host-based
Intrusion Detection Systems into the Tivoli
Enterprise Console, Christian Gigandet (IBM
Research Zurich Research Laboratory)
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Cisco Intrusion Detection System NetSonar
(Scanner) NetRanger (Monitor)

• The Cisco Secure IDS includes two components
  Sensor (renamed NetSonar) and Director (renamed
  NetRanger).
• Cisco Secure IDS Sensors, which are high-speed
  network "appliances," analyze the content and
  context of individual packets to determine if
  traffic is authorized.

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(No Transcript)
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ISS

• RealSecure
• Network engine resides on PC, monitors network
  transmissions for signs of abuse and attack
• About 350 attack signatures currently published

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APIs solve top 4 problems

• ID module embedded in router/switch/firewall
• Evaluates all incoming and outgoing traffic for
  intrusions across all ports
• Switching. Monitors heavily routed or switched
  networks at the most heavily-trafficked network
  junctions.
• Speed. May also address speed issues by embedding
  ID in higher-performance hardware.
• ID module running on adapter card
• Processor provides most of the analysis.
• Speed. Hardware assist with packet classification
  provides wire-speed intrusion detection.
• Security is painful. Shrink-wrap ID engine --
  easy to install, easy to manage with relatively
  low cost.
• ID module as an ASIC
• ID as a true design component. Installed on
  networking backplane, e.g. multi-gigabit switch,
  Probably only way to handle
• Switching. Embedded in high-performance network
  device allows access to all packets at single
  location.
• Speed. Wire-speed intrusion detection.
• ID module embedded in host protocol stack
• Attached to protocol stack above encryption
  layer.
• Encryption. Allows intrusion detection to exist
  in the presence of encrypted traffic while still
  providing adequate value.

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CyberSafe Centrax
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Summary

• Maintain integrity
• Per layer
• Per slice (protocol)
• Validate packets
• Ingress/egress counters
• Squelch attack sources that do not comply with
  reasonable usage
• Test carefully to ensure not a new application
• Streaming media is not a UDP attack!
• Measure and understand flow properties
• Recognize statistically significant variation
  from these path properties

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Backup Slides
A bit more formality A glimpse at some academic
research
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Assumptions

• Assumptions
• RFC 1636 encryption essential to security
• Open networks violate this assumption
• Encryption should protect control information, as
  well as contents
• In attack from Vi ? net ? Vj assume only one of
  Vi, Vj is the attacker
• DDOS violates this assumption
• Assumptions are sometimes wrong
• Replay attack can masquerade with encrypted data
• Distributed attacks can leverage multiple
  attackers
• Encryption can be broken

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General Network Model(circumscribes problem
domain)

• G (V, E)
• Path Vin, Ej, Vj, Ek, Vk, El,
  Vout
• Path consists of vertices and edges
• Edges E
• Propagate signal
• Vertices V
• Receive signal
• Compute output
• Emit signal

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Network Model

• Edges (links)
• Signal propagation
• Impairments due to random noise
• Redundancy manages noise, fade or analog error
• Detect and correct by protocols through algebraic
  redundancy
• Vertices (routers/switches)
• Aggregate bits into packet
• Classify and enqueue packet
• Packet-type and priority (UDP? TCP? ICMP? RSVP?)
• Loss due to load variation and queue size
• Detect and correct by redundant payload or
  retransmission
• Dequeue packet
• Data packet compute output as f(packet, control)
• Control packet modify control as f(packet,
  control)

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Vertex Control function f(packet,control)

• Data packet
• Pure IP f(packet, control) is nearly the
  identity function
• modify TTL, next-hop, etc
• Proxy or active protocol f(packet, control) not
  identity
• Augment packets in more complex custom ways
• Control packets
• Routing static or dynamic
• Resource modify resources, i.e. queues,
  priorities
• Behavior modify function, i.e. classifier,
  marking, etc.

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Monitoring Entity Signatures

• Entity output descriptions
• Compute usage signatures (local and complete)
• Entity to neighbors
• Entity to endpoints
• Entity input descriptions
• Receivers compute signature of received data
• Comparisons
• Entities exchange signatures (or log centrally)
• Anomaly detected from signature mismatches

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JiNao Protect Link-State Routing
Finite state machine with timing analysis,
verifies Validity of OSPF actions, and guards
against any intrusion even one with valid
security credentials