Highintegrity Sensor Networks

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High-integrity Sensor Networks

• Mani Srivastava
• mbs_at_ucla.edu
• UCLA

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High Integrity Sensor Networks
Information returned may be distorted
NEW FOCUS
Malicious attack (privacy, denial ofservice,
corruption)

• Noise random error, unavoidable
• In the sensor
• In communication

Fault Persistent,transient,intermittent
malfunction
Hard to counterEasy to learn
Easy to counterHard to learn
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Key Issues and Challenges

• Sensor nodes have to be cheap
• Fault-tolerant, secure hardware not feasible
• Unmanned and untethered
• No central supervision
• Severe resource constraints
• Limited memory, CPU, b/w
• Scale
• Collaborative behavior
• Decentralized in-networkprocessing for energy
  efficiency
• Open wireless medium

Handle misbehaving nodes
Existing solutions not portable
End-to-End Model?
Robust Relaying
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Spectrum of Integrity Problems
Misbehaving Node
Misbehavior while routing event
report Well-studied ad hoc routing problems
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Spectrum of Integrity Problems
It was a false alarm.No such car!
Misbehaving Node
Misbehavior during in-network processing (e.g.
generation of bad event, suppression of event)
Well-studied fault tolerant computing problems
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Spectrum of Integrity Problems
No car Detected
Misbehavior during information generation (e.g.
miscalibrated or compromised sensors)
No car Detected
Our focus!
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Approach Reputation-based Framework
Key Question How do nodes trust each other?
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Basic Concept - Learning from Experience
Watchdog mechanism
Reputation
Trust
Behavior
Second hand information

• Observe the action of other nodes Watchdog
  mechanism
• Develop a perception of other nodes over time
  Reputation
• Predict their future behavior Trust
• Cooperate/Non-cooperate with trustworthy nodes
  Behavior
• Share experiences to facilitate community growth
  Second hand info

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Skeleton Structure of RFSN
Watchdog mechanism
Reputation
Trust
Behavior
Second hand information
Algorithm Development Monitoring, Data
Analysis Statistics.
Networking,Cryptography
Decision theory Bayesian Analysis
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Bayesian Formulation of Sensor Integrity

• Reputation representation for neighbors as beta
  distribution
• two parameters (cooperation, non-cooperation)
• Easy to compute reputation updates and
  integration using belief theory
• Updates
• Integration
• Reputation propagation via public key crypto for
  node authentication
• Trust to estimate future cooperative behavior q
  of node j with reputation Beta(aj, bj)
• Classifying node behavior as good/bad by simple
  threshold on trust

New reputation, ??
Old reputation, Beta(aj, bj)
????
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Conclusions

• Reputation-based approach is
• Scalable localized algorithms
• General communication, sensing, processing
• Unified faulty, malicious, noisy
• But insufficient for certain malicious attacks on
  integrity
• Context-aware adversaries
• Resource consumption attacks
• Compromises of the physical world

Network level techniques? Multimodality?
No Event
No Event