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

该项目解决了为身体区域网络(BAN)提供可用的(即插即用、自我配置和自主)安全解决方案的挑战：由经济实惠的、无线的、可穿戴的和/或植入的健康监测节点(传感器和执行器)组成的网络，用于收集和通信健康信息以及适当地管理药物或假体动作。禁令有许多不同的应用，包括运动健康管理、家庭保健和术后护理。由于收集的数据的敏感性，确保禁令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)方面需要相当大的设置努力。相比之下，该项目采用了一种网络物理方法，并使用了基于生理值的安全(PVS)的概念，该概念使用生理值(PV)来生成用于保护禁令的密钥。这个项目中的两个重要问题是：1)识别合适的PV以生成高质量的密钥；2)开发信号处理技术以从生理值生成密码密钥。对于前一个问题，使用常见的静脉曲张(例如，心电图仪、脉搏图等)将进行研究；对于后者，将开发时间域和频域特征生成技术。该项目将导致：a)选择合适的PV的基准，b)用于实时提取PV的轻量级测量和同步算法，c)在Impact实验室实现PVS的软硬件原型--S·阿育什曼普及健康监测试验台。这些结果(将在http://impact.asu.edu)上公开)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.