LDTS: A Lightweight and Dependable Trust Systemfor Clustered Wireless Sensor Networks

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Presented by: Ting Hua

Authors: Xiaoyong Li, Feng Zhou, and Junping Du

Outline

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• Motivation• Clustered WSN Model• Lightweight Scheme for Trust Decision-Making• Theoretical analysis and evaluation• Simulation-based analysis and evaluation• Conclusion

Motivation

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• Limited work focus on– Resource efficiency of clustered WSNs

• fail to consider the problem of resource constraints of nodes• used complex algorithms to calculate nodes’ trustworthiness

– Dependability of the trust system itself• Current: collect remote feedback and then aggregate s such

feedback to yield the global reputation for the nodes• Problem: How about open or hostile WSN environment

contains a large number of undependable (or malicious) nodes?

Outline

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• Motivation• Clustered WSN Model• Lightweight Scheme for Trust Decision-Making• Theoretical analysis and evaluation• Simulation-based analysis and evaluation• Conclusion

Clustered WSN Model

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• Nodes– CH: cluster head – CM: cluster member– BS: base station

• Communications– Inter-cluster: A CM can communicate

with their CH directly.– Intra-cluster: A CH can forward the

aggregated data to the central BS through other CHs.

Outline

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• Motivation• Clustered WSN Model• Lightweight Scheme for Trust Decision-Making• Theoretical analysis and evaluation• Simulation-based analysis and evaluation• Conclusion

Trust Decision-Making at CM Level

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• Decision making: past interaction records?– Yes: CM-to-CM Direct trust degree (DTD)

• # of successful and unsuccessful interactions• Interaction: cooperation of two CMs, e.g., node x sends a

message to CH i via node y– Successful: node y forwarded such message to CH – Unsuccessful:

» No retransmission of the packet within a threshold time» Overheard packet is illegally fabricated

– No: CH-to-CM Indirect trust degree (ITD)• send a feedback request to CH

CM-to-CM Direct Trust Calculation

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a window of time # of successful interactions of node x with y

# of unsuccessful interactions of node x with y strict punishment for

unsuccessful interactions

CH-to-CM Feedback Trust Calculation

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# of positive feedback

# of negativefeedback

Assumption: CH is trustworthy within its cluster!

Trust Decision-Making at CH Level

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• Decision making: calculate for direct trust and feedback trust simultaneously

• CH-to-CH direct trust– # of successful and unsuccessful interactions

• BS-to-CH feedback trust– BS periodically asks all CHs for their trust ratings on their neighbors.– CH send a feedback request to BS

CH-to-CH Direct Trust Calculation

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# of unsuccessful interactions of CH i with CH j strict punishment for

unsuccessful interactions

a window of time # of successful interactions of CH i with CH j

BS-to-CH Feedback Trust Calculation

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feedback of CH k toward CH j

# of positive feedback

# of negativefeedback

quality of feedback

Self-Adaptive Global Trust Aggregation at CHs

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# of successful interactions

BS-to-CH feedback trust

CH-to-CH Direct Trust

# of positive feedbacks

increasing α, Φ(x) quickly approaches 1

Outline

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• Motivation• Clustered WSN Model• Lightweight Scheme for Trust Decision-Making• Theoretical analysis and evaluation• Simulation-based analysis and evaluation• Conclusion

Dependability Analysis Against Malicious Attacks

Dependability Analysis Against Malicious Attacks

Dependability Analysis Against Malicious Attacks

Dependability Analysis Against Malicious Attacks

Dependability Analysis Against Malicious Attacks

Dependability Analysis Against Malicious Attacks

Dependability Analysis Against Malicious Attacks

Dependability Analysis Against Malicious Attacks

Dependability Analysis Against Malicious Attacks

Dependability Analysis Against Malicious Attacks

Communication Overhead Analysis and Comparison

Assume: Network consists of m clusters (including the BS)average size of clusters is n (including the CH of the cluster)

# of CM send n requests and receiven responses

communication overhead of one node

Storage Overhead Analysis and Comparison

Outline

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• Motivation• Clustered WSN Model• Lightweight Scheme for Trust Decision-Making• Theoretical analysis and evaluation• Simulation-based analysis and evaluation• Conclusion

LDTS Simulator and Environment

Overhead Evaluation and Comparison

Overhead Evaluation and Comparison

Dependability Evaluation and Comparison

Dependability Evaluation and Comparison

Outline

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• Motivation• Clustered WSN Model• Lightweight Scheme for Trust Decision-Making• Theoretical analysis and evaluation• Simulation-based analysis and evaluation• Conclusion

Conclusion

• Lightweight trust evaluating scheme – cooperations between CMs – cooperations between CHs

• Dependability-enhanced trust evaluating approach – cooperations between CHs

• Self-adaptive weighting method – CH’s trust aggregation