MobiHoc '01 Proceedings of the 2nd ACM international symposium on Mobile ad hoc networking & computing
A key-management scheme for distributed sensor networks
Proceedings of the 9th ACM conference on Computer and communications security
Random Key Predistribution Schemes for Sensor Networks
SP '03 Proceedings of the 2003 IEEE Symposium on Security and Privacy
A pairwise key pre-distribution scheme for wireless sensor networks
Proceedings of the 10th ACM conference on Computer and communications security
Establishing pairwise keys in distributed sensor networks
Proceedings of the 10th ACM conference on Computer and communications security
Location-based pairwise key establishments for static sensor networks
Proceedings of the 1st ACM workshop on Security of ad hoc and sensor networks
A cooperative intrusion detection system for ad hoc networks
Proceedings of the 1st ACM workshop on Security of ad hoc and sensor networks
Location-aware key management scheme for wireless sensor networks
Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks
Revisiting random key pre-distribution schemes for wireless sensor networks
Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks
Optimal Resource Allocation in Wireless Ad Hoc Networks: A Price-Based Approach
IEEE Transactions on Mobile Computing
Sufficient rate constraints for QoS flows in ad-hoc networks
Ad Hoc Networks
ACM Transactions on Information and System Security (TISSEC)
Simulation modeling of secure wireless sensor networks
Proceedings of the Fourth International ICST Conference on Performance Evaluation Methodologies and Tools
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We study the applicability of random graph theory in modeling secure connectivity of wireless sensor networks. Specifically, our work focuses on the highly influential random key predistribution scheme by Eschenauer and Gligor to examine the appropriateness of the modeling in finding system parameters for desired connectivity. We use extensive simulation and theoretical results to identify ranges of the parameters where i) random graph theory is not applicable, ii) random graph theory may lead to estimates with excessive errors, and iii) random graph theory gives very accurate results. We also investigate the similarities and dissimilarities in the structure of random graphs and key graphs (i.e., graphs describing key sharing information between sensor nodes). Our results provide insights into research relying on random graph modeling to examine behaviors of key graphs.