E-health is a growing eld which utilizes wireless sensor networks to enable access to effective and efficient healthcare services and provide patient monitoring to enable early detection and treatment of health conditions. Due to the proliferation of e-health systems, security and privacy have become critical issues in preventing data falsification, unauthorized access to the system, or eavesdropping on sensitive health data. Furthermore, due to the intrinsic limitations of many wireless medical devices, including low power and limited computational resources, security and device performance can be difficult to balance. Therefore, many current networked medical devices operate without basic security services such as authentication, authorization, and encryption.
In this work, we survey recent work on e-health security, including biometric approaches, proximity-based approaches, key management techniques, audit mechanisms, anomaly detection, external device methods, and lightweight encryption and key management protocols. We also survey the state-of-the art in e-health privacy, including techniques such as obfuscation, secret sharing, distributed data mining, authentication, access control, blockchain, anonymization, and cryptography. We then propose a comprehensive system model for e-health applications with consideration of battery capacity and computational ability of medical devices. A case study is presented to show that the proposed system model can support heterogeneous medical devices with varying power and resource constraints. The case study demonstrates that it is possible to signicantly reduce the overhead for security on power-constrained devices based on the proposed system model.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-3633 |
| Date | 01 June 2020 |
| Creators | Jellen, Isabel |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
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