Chimera: AVirtual Data System for Representing, Querying, and Automating Data Derivation
SSDBM '02 Proceedings of the 14th International Conference on Scientific and Statistical Database Management
A survey of data provenance in e-science
ACM SIGMOD Record
Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks
Provenance-based trustworthiness assessment in sensor networks
Proceedings of the Seventh International Workshop on Data Management for Sensor Networks
Preserving integrity and confidentiality of a directed acyclic graph model of provenance
DBSec'10 Proceedings of the 24th annual IFIP WG 11.3 working conference on Data and applications security and privacy
Towards low overhead provenance tracking in near real-time stream filtering
IPAW'06 Proceedings of the 2006 international conference on Provenance and Annotation of Data
IEEE Communications Magazine
Securing data provenance in body area networks using lightweight wireless link fingerprints
Proceedings of the 3rd international workshop on Trustworthy embedded devices
Securing data provenance in body area networks using lightweight wireless link fingerprints
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
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The popularity of sensor networks and their many uses in critical domains such as military and healthcare make them more vulnerable to malicious attacks. In such contexts, trustworthiness of sensor data and their provenance is critical for decision-making. In this demonstration, we present an efficient and secure approach for transmitting provenance information about sensor data. Our provenance approach uses light-weight in-packet Bloom filters that are encoded as sensor data travels through intermediate sensor nodes, and are decoded and verified at the base station. Our provenance technique is also able to defend against malicious attacks such as packet dropping and allows one to detect the responsible node for packet drops. As such it makes possible to modify the transmission route to avoid nodes that could be compromised or malfunctioning. Our technique is designed to create a trustworthy environment for sensor nodes where only trusted data is processed.