Probabilistic counting algorithms for data base applications
Journal of Computer and System Sciences
LOF: identifying density-based local outliers
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
TAG: a Tiny AGgregation service for ad-hoc sensor networks
ACM SIGOPS Operating Systems Review - OSDI '02: Proceedings of the 5th symposium on Operating systems design and implementation
SIA: secure information aggregation in sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
Reputation-based framework for high integrity sensor networks
Proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks
LCN '04 Proceedings of the 29th Annual IEEE International Conference on Local Computer Networks
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
SDAP: a secure hop-by-Hop data aggregation protocol for sensor networks
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Secure hierarchical in-network aggregation in sensor networks
Proceedings of the 13th ACM conference on Computer and communications security
An efficient integrity-preserving scheme for hierarchical sensor aggregation
WiSec '08 Proceedings of the first ACM conference on Wireless network security
Reputation-based framework for high integrity sensor networks
ACM Transactions on Sensor Networks (TOSN)
SIA: Secure information aggregation in sensor networks
Journal of Computer Security - Special Issue on Security of Ad-hoc and Sensor Networks
P2P reputation management: Probabilistic estimation vs. social networks
Computer Networks: The International Journal of Computer and Telecommunications Networking - Management in peer-to-peer systems
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In this paper we present an efficient trust-aware in-network aggregation approach for resilient wireless sensor networks. The work is motivated from the well studied reputation and trust relations in the field of social sciences. In our approach, the trust evaluation mechanism is applied to identify trustworthiness of sensor nodes, distinguish illegal/misbehaving nodes, and filter out bogus data in the aggregation process. The objective of this effort is to return the highest-fidelity possible response to the user, while monitoring the health of the network by flagging suspected compromised nodes. The experimental results demonstrate the effectiveness of the proposed approach.