Cleaning and querying noisy sensors
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
IEEE Transactions on Computers
Proceedings of the 3rd international conference on Embedded networked sensor systems
Connected sensor cover: self-organization of sensor networks for efficient query execution
IEEE/ACM Transactions on Networking (TON)
Online outlier detection in sensor data using non-parametric models
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Effective variation management for pseudo periodical streams
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
SenseWorld: Towards Cyber-Physical Social Networks
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Cyber Physical Systems: Design Challenges
ISORC '08 Proceedings of the 2008 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing
Cyber-Physical Systems: A New Frontier
SUTC '08 Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008)
CarWeb: A Traffic Data Collection Platform
MDM '08 Proceedings of the The Ninth International Conference on Mobile Data Management
A Robust Sampling-Based Framework for Privacy Preserving OLAP
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Acoustic sensor network design for position estimation
ACM Transactions on Sensor Networks (TOSN)
Sensor network data fault types
ACM Transactions on Sensor Networks (TOSN)
Filtering and Refinement: A Two-Stage Approach for Efficient and Effective Anomaly Detection
ICDM '09 Proceedings of the 2009 Ninth IEEE International Conference on Data Mining
A secure multiparty computation privacy preserving OLAP framework over distributed XML data
Proceedings of the 2010 ACM Symposium on Applied Computing
An event driven framework for assistive CPS environments
ACM SIGBED Review - Special Issue on the 2nd Joint Workshop on High Confidence Medical Devices, Software, and Systems (HCMDSS) and Medical Device Plug-and-Play (MD PnP) Interoperability
Balancing accuracy and privacy of OLAP aggregations on data cubes
DOLAP '10 Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
Tru-Alarm: Trustworthiness Analysis of Sensor Networks in Cyber-Physical Systems
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
A Survey of Outlier Detection Methods in Network Anomaly Identification
The Computer Journal
Journal of Computer and System Sciences
Declarative support for sensor data cleaning
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
Outlier Detection Techniques for Wireless Sensor Networks: A Survey
IEEE Communications Surveys & Tutorials
Security similarity based trust in cyber space
Knowledge-Based Systems
SIREN: a feasible moving target defence framework for securing resource-constrained embedded nodes
International Journal of Critical Computer-Based Systems
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A Cyber-Physical System (CPS) is an integration of sensor networks with informational devices. CPS can be used for many promising applications, such as traffic observation, battlefield surveillance, and sensor-network-based monitoring. One key issue in CPS research is trustworthiness analysis of sensor data. Due to technology limitations and environmental influences, the sensor data collected by CPS are inherently noisy and may trigger many false alarms. It is highly desirable to sift meaningful information from a large volume of noisy data. In this study, we propose a method called Tru-Alarm, which increases the capability of a CPS to recognize trustworthy alarms. Tru-Alarm estimates the locations of objects causing alarms, constructs an object-alarm graph and carries out trustworthiness inference based on the graph links. The study also reveals that the alarm trustworthiness and sensor reliability could be mutually enhanced. The property is used to help prune the large search space of object-alarm graph, filter out the alarms generated by unreliable sensors and improve the algorithm@?s efficiency. Extensive experiments are conducted on both real and synthetic datasets, and the results show that Tru-Alarm filters out noise and false information efficiently and effectively, while ensuring that no meaningful alarms are missed.