CT-ISG: Physiological Value based Security for Body Area Networks

该项目解决了为身体区域网络（ban）提供可用（即插即用、自配置和自主）安全解决方案的挑战：经济供电、无线、可穿戴和/或植入健康监测节点（传感器和执行器）的网络，用于收集和通信健康信息，并适当地管理药物或假肢动作。ban有许多不同的应用，包括运动健康管理、家庭保健和手术后护理。由于所收集数据的敏感性，确保ban对于保护隐私和保护主机免受身体伤害非常重要。传统的安全方法在预先部署加密秘密（密钥分发）方面需要大量的设置工作。相比之下，该项目采用网络物理方法并使用基于生理值的安全性（PVS）的概念，该概念使用生理值（pv）来生成加密密钥以保护ban。本项目中的两个重要问题是：1)识别用于生成高质量密钥的合适pv；2)从生理值生成密码密钥的信号处理技术的发展。对于前一个问题，将研究使用常见的pv（如心电图、光电容积图等）；对于后者，将开发时域和频域特征生成技术。该项目将产生：a)选择合适pv的基准，b)实时提取pv的轻量级测量和同步算法，c) IMPACT实验室中pv的软件和硬件（基于fpga）原型实现？AYUSHMAN普适健康监测试验台。这些结果（将在http://impact.asu.edu公开发布）将是朝着为所有人提供可靠、负担得起的医疗保健迈出的重要一步。

This project addresses the challenge of providing usable (plug-and-play, self-configuring, and autonomic) security solutions for Body Area Networks (BANs): networks of economically powered, wireless, wearable and/or implanted health monitoring nodes (sensors and actuators), for collecting and communicating health information and, appropriately administering medicine or prosthetic actions. BANs have many diverse applications including sports health management, home-based health-care and post-operative care. Due to the sensitive nature of the data collected, securing BANs is important for privacy preservation and protecting the host from bodily harm. Traditional security methods require considerable setup efforts in terms of pre-deployment of cryptographic secrets (key distribution). In contrast, this project takes a cyber-physical approach and uses the concept of Physiological Value based Security (PVS), which employs physiological values (PVs) to generate cryptographic keys for securing BANs. Two important issues in this project are: 1) identification of appropriate PVs for generating high-quality keys; and 2) development of signal processing techniques to generate cryptographic keys from the physiological values. For the former issue, the use of common PVs (e.g. Electrocardiogram, Photoplethysmogram, etc.) would be investigated; for the latter, time and frequency domain feature generation techniques would be developed. This project will result in: a) benchmarks for selecting appropriate PVs, b) light-weight measurement and synchronization algorithms to extract PVs in real-time, c) a software and hardware (FPGA-based) prototype implementation of PVS in IMPACT lab?s AYUSHMAN pervasive health monitoring testbed. These results (to be made publicly available at http://impact.asu.edu) will be an important step toward providing dependable, affordable healthcare for all.