Intrusion Detection in Wireless Sensor Networks

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Intrusion Detection in Wireless Sensor Networks

• Group Meeting
• Spring 2005
• Presented by Edith Ngai

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Outline

• Wireless sensor networks (WSN)
• Security in WSN
• Background on intrusion detection
• Intrusion detection in WSN
• Types of attacks
• Intrusion detection components
• Required technologies
• Future directions
• Conclusion

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Technology trend

• Small integrated devices
• Smaller, cheaper, more powerful
• PDAs, mobile phones
• Many opportunities, and research areas
• Power management
• Distributed algorithms

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Wireless sensor networks

• Wireless sensor node
• power supply
• sensors
• embedded processor
• wireless link
• Many, cheap sensors
• wireless ? easy to install
• intelligent ? collaboration
• low-power ? long lifetime

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Possible applications

• Military
• battlefield surveillance, biological attack
  detection, targeting
• Ecological
• fire detection, flood detection, agricultural
  uses
• Health related
• human physiological data monitoring
• Miscellaneous
• car theft detection, inventory control, home
  applications

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Required technologies

• Efficient data routing
• ad-hoc network
• one or more datasinks
• In-network data processing
• large amounts of raw data
• limited power and bandwidth
• Node localization

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Security in WSN

• Main security threats in WSN are
• Radio links are insecure eavesdropping /
  injecting faulty information is possible
• Sensor nodes are not temper resistant if it is
  compromised the attacker obtains all security
  information
• Protecting confidentiality, integrity, and
  availability of the communications and
  computations

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Why security is different?

• Sensor Node Constraint
• Battery
• CPU power
• Memory
• Networking Constraints and Features
• Wireless
• Ad hoc
• Unattended

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Network defense
React - Response - Terminate Connections
- Block IP Addresses - Containment -
Recovery - Reconstitute
Protect - Encryption - Firewalls -
Authentication - Biometrics
Detect - Intrusions - Attacks - Misuse of
Resources - Data Correlation - Data
Visualization - Malicious Behaviors - Network
Status/ Topology
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What is intrusion detection?

• Intrusion detection is the process of
  discovering, analyzing, and reporting
  unauthorized or damaging network or computer
  activities
• Intrusion detection discovers violations of
  confidentiality, integrity, and availability of
  information and resources

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What is intrusion detection?

• Intrusion detection demands
• As much information as the computing resources
  can possibly collect and store
• Experienced personnel who can interpret network
  traffic and computer processes
• Constant improvement of technologies and
  processes to match pace of Internet innovation

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How useful is intrusion detection?

• Provide digital forensic data to support
  post-compromise law enforcement actions
• Identify host and network misconfigurations
• Improve management and customer understanding of
  the Internet's inherent hostility
• Learn how hosts and networks operate at the
  operating system and protocol levels

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Intrusion detection models

• All computer activity and network traffic falls
  in one of three categories
• Normal
• Abnormal but not malicious
• Malicious
• Properly classifying these events are the single
  most difficult problem -- even more difficult
  than evidence collection

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Intrusion detection models

• Two primary intrusion detection models
• Network-based intrusion detection monitors
  network traffic for signs of misuse
• Host-based intrusion detection monitors computer
  processes for signs of misuse
• So-called "hybrid" systems may do both
• A hybrid IDS on a host may examine network
  traffic to or from the host, as well as processes
  on that host

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IDS paradigms

• Anomaly Detection - the AI approach
• Misuse Detection - simple and easy
• Burglar Alarms - policy based detection
• Honey Pots - lure the hackers in
• Hybrids - a bit of this and that

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Anomaly detection

• Goals
• Analyze the network or system and infer what is
  normal
• Apply statistical or heuristic measures to
  subsequent events and determine if they match the
  model/statistic of normal
• If events are outside of a probability window of
  normal then generate an alert

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Misuse detection

• Goals
• Know what constitutes an attack
• Detect it
• A database of known attack signatures should be
  maintained

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Intrusion Detection in WSN
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Network model

• BSj base station at location (Xj, Yj)
• Si sensor node at location (xi, yi)
• R transmission range of the base station
• r transmission range of the sensor node
• k-coverage a node covers by k BSs

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Definitions

• Coverage of a base station
• Number of coverage from base stations
• p sends data to q successfully (in 1-hop)
• p sends data to q successfully via k hops
• p fails in sending data from p to q

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Types of intrusions

• Sinkhole SH(q), HelloFlood HF(q)
• A region of nodes will forward packets destined
  for a BS through an adversary
• Wormhole WH(q)
• An adversary tunnels messages received in one
  part of the network over a low latency link and
  replays them in a different part

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Types of intrusions

• Missing Data MD(p)
• Missing data from p to BSi
• Wrong Data WD(p)
• Inconsistent data
• Interference
• Sensor p cannot send packet to its neighboring
  nodes

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Architecture
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Intrusion detection components

• Neighbor monitoring
• Watchdog
• Data fusion
• Local neighboring nodes
• Global overlapping areas
• Topology discovery
• Route tracing
• History

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Intrusion classification
Components\Attack Types Components\Attack Types I II III IV V
Neighbor Monitoring BS Dominating intermediate node Dominating intermediate node Selective forwarding --- ---
Neighbor Monitoring Sensor --- --- Selective forwarding --- Interference (jamming with neighbors)
Data Comparison Global (may have missing or inconsistent data) (may have missing or inconsistent data) Missing data Inconsistent data (IVa malicious sensor or intermediate nodes) Missing data
Data Comparison Local (may have missing or inconsistent data) (may have missing or inconsistent data) Missing data Inconsistent data (IVb sensor failure or being compromised) Missing data
Routing (with topology info.) BS a region of nodes forward packet through the same adversary An adversary tunnels messages and replays them in a different part --- --- ---
Attack Types I - Sinkhole, Hello Flood II
Wormhole III Missing Data IV Wrong
Data V - Interference
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Required technologies

• Collection of the audit data
• Localization
• Data fusion
• Routing
• Analysis on the audited data
• Identify the intrusion characteristics
• Detect the intrusions
• Locate the intrusions
• Intrusion reaction

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Future direction

• Study how to collect the audit data effectively
• Complete the intrusion detection architecture
• Investigate the methods to analyze the audit data
  for intrusion detection
• Explore how to locate and react to the intrusions
• Formulate and evaluate our intrusion detection
  solution

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Conclusion

• We discussed the characteristics of WSN and its
  security issues
• We studied traditional intrusion detection
  technologies
• We introduced the problem of intrusion detection
  in WSN
• We proposed an intrusion detection architecture
  and analyzed various kinds of intrusions in WSN
• We showed our future direction