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Báo cáo hóa học: " Research Article Biometric Methods for Secure Communications in Body Sensor Networks: Resource-Efficient Key Management and Signal-Level Data "

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Biometric Methods for Secure Communications in Body Sensor Networks: Resource-Efficient Key Management and Signal-Level Data | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2008 Article ID 529879 16 pages doi 10.1155 2008 529879 Research Article Biometric Methods for Secure Communications in Body Sensor Networks Resource-Efficient Key Management and Signal-Level Data Scrambling Francis Minhthang Bui and Dimitrios Hatzinakos The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto 10 King s College Road Toronto Ontario Canada M5S 3G4 Correspondence should be addressed to Dimitrios Hatzinakos dimitris@comm.utoronto.ca Received 1 June 2007 Revised 28 September 2007 Accepted 21 December 2007 Recommended by Juwei Lu As electronic communications become more prevalent mobile and universal the threats of data compromises also accordingly loom larger. In the context of a body sensor network BSN which permits pervasive monitoring of potentially sensitive medical data security and privacy concerns are particularly important. It is a challenge to implement traditional security infrastructures in these types of lightweight networks since they are by design limited in both computational and communication resources. A key enabling technology for secure communications in BSN s has emerged to be biometrics. In this work we present two complementary approaches which exploit physiological signals to address security issues 1 a resource-efficient key management system for generating and distributing cryptographic keys to constituent sensors in a BSN 2 a novel data scrambling method based on interpolation and random sampling that is envisioned as a potential alternative to conventional symmetric encryption algorithms for certain types of data. The former targets the resource constraints in BSN s while the latter addresses the fuzzy variability of biometric signals which has largely precluded the direct application of conventional encryption. Using electrocardiogram ECG signals as biometrics the resulting computer simulations .