Imperial College London

DrDavidBoyle

Faculty of EngineeringDyson School of Design Engineering

Lecturer
 
 
 
//

Contact

 

+44 (0)20 7594 8172david.boyle CV

 
 
//

Location

 

Dyson BuildingSouth Kensington Campus

//

Summary

 

Publications

Publication Type
Year
to

46 results found

O'Connell E, O'Flynn B, Boyle D, 2013, Clocks, latency and energy efficiency in duty cycled, multi-hop Wireless Sensor Networks, 5th IEEE International Workshop on Advances in Sensors and Interfaces (IWASI), Publisher: IEEE, Pages: 199-204

Conference paper

Rosello V, Boyle D, Portilla J, O Flynn B, Riesgo Tet al., 2013, Route-back delivery protocol for Collection Tree Protocol-based applications, 10th European Conference on Wireless Sensor Networks (EWSN)

Poster

Barta L, Boyle D, O Flynn B, Popovici Eet al., 2013, Simplified Commissioning and Maintenance for Wireless Sensor Networks: a Novel Software Tool, Publisher: VDE VERLAG GmbH

Conference paper

Boyle D, Ramparany F, 2012, Data processing for managing the quality of service in a machine-to-machine network, WO2012080414A2

Patent

Boyle D, Srbinovski B, Popovici E, O Flynn Bet al., 2012, Energy analysis of industrial sensors in novel wireless SHM systems, Pages: 1-4

Conference paper

Buckley J, O Flynn B, Loizou L, Haigh P, Boyle D, Angove P, Barton J, O Mathuna C, Popovici E, O Connell Set al., 2012, A Novel and Miniaturized 433/868MHz Multi-band Wireless Sensor Platform for Body Sensor Network Applications, Pages: 63-66

Conference paper

Boyle D, Magno M, O Flynn B, Brunelli D, Popovici E, Benini Let al., 2011, Towards persistent structural health monitoring through sustainable wireless sensor networks, Publisher: IEEE, Pages: 323-328

Conference paper

Popovici E, Boyle D, O Connell S, Faul S, Angove P, Buckley J, O Flynn B, Barton J, O Mathuna Cet al., 2011, The s-Mote: A versatile heterogeneous multi-radio platform for wireless sensor networks applications, Pages: 421-424

Conference paper

O Flynn B, Boyle D, Popovici EM, Magno M, Petrioli Cet al., 2011, GENESI: Wireless sensor networks for structural monitoring

Conference paper

Newe T, Cionca V, Boyle D, 2010, Security for Wireless Sensor Networks–Configuration Aid, Advances in Wireless Sensors and Sensor Networks, Pages: 1-24

Journal article

Boyle DE, Newe T, 2009, On the implementation and evaluation of an elliptic curve based cryptosystem for Java enabled Wireless Sensor Networks, Sensors and Actuators A: Physical, Vol: 156, Pages: 394-405

Journal article

Boyle D, Newe T, 2008, The Impact of Java and Public Key Cryptography in Wireless Sensor Networking, Pages: 288-293

Conference paper

Boyle D, Newe T, 2008, Securing wireless sensor networks: security architectures, Journal of Networks, Vol: 3, Pages: 65-77

Journal article

Boyle D, Newe T, 2007, A Survey of Authentication Mechanisms: Authentication for Ad-Hoc Wireless Sensor Networks, Sensors Applications Symposium SAS '07

Conference paper

Aloufi R, Haddadi H, Boyle D, Privacy-preserving Voice Analysis via Disentangled Representations

Voice User Interfaces (VUIs) are increasingly popular and built intosmartphones, home assistants, and Internet of Things (IoT) devices. Despiteoffering an always-on convenient user experience, VUIs raise new security andprivacy concerns for their users. In this paper, we focus on attributeinference attacks in the speech domain, demonstrating the potential for anattacker to accurately infer a target user's sensitive and private attributes(e.g. their emotion, sex, or health status) from deep acoustic models. Todefend against this class of attacks, we design, implement, and evaluate auser-configurable, privacy-aware framework for optimizing speech-related datasharing mechanisms. Our objective is to enable primary tasks such as speechrecognition and user identification, while removing sensitive attributes in theraw speech data before sharing it with a cloud service provider. We leveragedisentangled representation learning to explicitly learn independent factors inthe raw data. Based on a user's preferences, a supervision signal informs thefiltering out of invariant factors while retaining the factors reflected in theselected preference. Our experimental evaluation over five datasets shows thatthe proposed framework can effectively defend against attribute inferenceattacks by reducing their success rates to approximately that of guessing atrandom, while maintaining accuracy in excess of 99% for the tasks of interest.We conclude that negotiable privacy settings enabled by disentangledrepresentations can bring new opportunities for privacy-preservingapplications.

Journal article

This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.

Request URL: http://wlsprd.imperial.ac.uk:80/respub/WEB-INF/jsp/search-html.jsp Request URI: /respub/WEB-INF/jsp/search-html.jsp Query String: id=00776155&limit=30&person=true&page=2&respub-action=search.html