LDTS: A Lightweight and Dependable Trust System for Clustered Wireless Sensor Networks 1 Presented by: Ting Hua Authors: Xiaoyong Li, Feng Zhou, and Junping Du

Outline 2 Motivation Clustered WSN Model Lightweight Scheme for Trust Decision-Making Theoretical analysis and evaluation Simulation-based analysis and evaluation Conclusion

Motivation 3 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 4 Motivation Clustered WSN Model Lightweight Scheme for Trust Decision-Making Theoretical analysis and evaluation Simulation-based analysis and evaluation Conclusion

Clustered WSN Model 5 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 6 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 7 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 8 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 9 # of positive feedback # of negative feedback Assumption: CH is trustworthy within its cluster!

Trust Decision-Making at CH Level 10 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 11 # 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 12 feedback of CH k toward CH j # of positive feedback # of negative feedback quality of feedback

Self-Adaptive Global Trust Aggregation at CHs 13 # of successful interactions BS-to-CH feedback trust CH-to-CH Direct Trust # of positive feedbacks increasing α, Φ(x) quickly approaches 1

Outline 14 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

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 receive n responses communicati on overhead of one node

Storage Overhead Analysis and Comparison

Outline 27 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

Dependability Evaluation and Comparison

Outline 33 Motivation Clustered WSN Model Lightweight Scheme for Trust Decision-Making Theoretical analysis and evaluation Simulation-based analysis and evaluation 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