ABSTRACT
Ayushman is a pervasive health monitoring system which has the ability to collect, process, store and display health data in a secure and easy to use manner. Recent years have seen considerable activity in this field. Most of these systems tend to treat health monitoring as an extension to generic sensor networks. and depend on a network of wearable and implanted, medical and ambient sensors (called a body area network) for data collection and transport. We contend that this paradigm is not suitable for medical monitoring given the low reliability of the sensors, and the mission critical nature of medical monitoring. Further, the existing systems mainly focus on patient monitoring and do not consider security at all, and those that do, treat it in an isolated manner. With Ayushman we present a system which addresses both these issues. It integrates sensors and highly capable entities in the back-end to provide robust health monitoring. It also considers security as an integral part of its design. Sensors in Ayushman utilize physiological values based security for securing their communication. Our design approach enables Ayushman to provide health monitoring in a secure and usable manner - a property that traditional systems lack.
- Intel Proactive Health. http://www.intel.com/research/prohealth/.Google Scholar
- S. Cherukuri, K. Venkatasubramanian, and S. K. S. Gupta. BioSec: A Biometric Based Approach for Securing Communication in Wireless Networks of Biosensors Implanted in the Human Body. pages 432--439, October 2003. In Proc. of Wireless Security and Privacy Workshop.Google Scholar
- D. Halperin and T. S. Heydt-Benjamin and B. Ransford and S. S. Clark and B. Defend and W. Morgan and K. Fu and T. Kohno and W. H. Maisel. Pacemakers and Implantable Cardiac Defibrillators: Software Radio Attacks and Zero-Power Defenses. 2008. In Proc. of IEEE Symposium on Security and Privacy. Google ScholarDigital Library
- L. Eschenauer and V. D. Gligor. A Key-Management Scheme for Distributed Sensor Networks. pages 41--47, November 2002. In Proc. of the 9th ACM conference on Computer and Communications Security. Google ScholarDigital Library
- E. Jovanov, A. Milenkovic, C. Otto, and P. C. de Groen. A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. Journal of NeuroEngineering and Rehabilitation, 2(6), March 2005.Google Scholar
- K. V. Laerhoven and H. W. Gellersen. Spine versus Porcupine: A Study in Distributed Wearable Activity Recognition. pages 142--149, Oct 2004. In Proc. of 8th Int. Symposium on Wearable Computers. Google ScholarDigital Library
- P. Lukowicz, U. Anliker, J. Ward, G. Tröster, E. Hirt, and C. Neufelt. AMON: A Wearable Medical Computer for High Risk Patients. pages 133--134, October 2002. In Proc. of IEEE 6th Int. Symposium on Wearable Computers. Google ScholarDigital Library
- A. Perrig, R. Szewczyk, V. Wen, D. Culler, and D. Tygar. SPINS: Security Protocol for Sensor Networks. Wireless Networks, 8(5):521--534, September 2002. Google ScholarDigital Library
- K. Venkatasubramanian, A. Banerjee, and S. K. S. Gupta. EKG-based Key Agreement in Body Sensor Networks. April 2008. In Proc. of the 2nd Workshop on Mission Critical Nets.Google Scholar
- K. Venkatasubramanian and et al. Ayushman: A Wireless Sensor Network Based Health Monitoring Infrastructure and Testbed. pages 406--407, June/July 2005. In Proc. of the IEEE Int. Conf. on Dist. Comp. in Sensor Sys. Google ScholarDigital Library
- K. Venkatasubramanian and S. K. S. Gupta. Security for Pervasive Health Monitoring Sensor Applications. pages 197--202, December 2006. In Proc. of the 4th Int. Conf. on Intell. Sensing and Infor. Processing (ICISIP, 2006).Google Scholar
- Victor Shnayder and Bor-rong Chen and Konrad Lorincz and Thaddeus R. F. Fulford-Jones, and Matt Welsh. Sensor Networks for Medical Care. April 2005. Harvard University Technical Report.Google Scholar
- G. Virone, A. Wood, L. Selavo, Q. Cao, L. Fang, T. Doan, Z. He, and J. Stankovic. An Assisted Living Oriented Information System Based on a Residential Wireless Sensor Network. April 2006. In Proc. of the Transdisciplinary Conference on Distributed Diagnosis and Home Healthcare.Google Scholar
- A. Wang and A. Chandrakasan. A 180-mv subthreshold FFT processor using a minimum energy design methodology. IEEE Journal on Solid State Circuits, 40(1):310--319, January 2005.Google ScholarCross Ref
- S. Zhu, S. Setia, and S. Jajodia. LEAP+: Efficient Security Mechanisms for Large-Scale Distributed Sensor Networks. ACM Transactions on Sensor Networks (TOSN), 2(4):500--528, November 2006. Google ScholarDigital Library
Index Terms
- Ayushman: a secure, usable pervasive health monitoring system
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