TWC: Small: Evidence of Presence for Intelligent Vehicles using Environment-Based Security

新兴的智能汽车将能够利用先进的车载传感器来支持新的应用，如污染检测、道路状况监测和交通控制。所有这些应用都需要能够验证阅读的位置和时间。该项目涉及设计核查方法，利用环境因素，如光线和阴影的存在和测量的无线信号强度，而不是传统的基于公钥基础设施的方法，以核查何时何地收集数据。 这种新的基于环境的模式可以抵御内部攻击，更容易部署，并保护个人车主的隐私。 这项研究将有助于实现应用程序所产生的越来越多的智能车辆在我们的道路上，可以造福公众的福祉。该项目还通过组织科学竞赛、全国大学生讲习班和夏季研究营活动，纳入了面向高中生和大学生的外联内容。 该项目是第一次尝试使用现代汽车的无线通信和视频记录能力来捕获自然环境特征，以安全地验证车辆网络设置中的时空声明。这是一项跨学科的研究工作，结合无线网络和计算机视觉来解决车载网络安全问题。项目的主要目标是：（1）探索新的视觉分析算法，以便识别由汽车摄像机捕获的图像的位置和时间;（2）研究用于识别用于位置消歧的最佳路边单元位置的新算法，以支持无线时空验证;（3）开发用于利用与公共车辆的相遇来验证时空声明的新技术;（4）开发一个融合框架，将联合收割机无线测量、车辆遭遇和视觉图像结合起来进行时空验证;以及（5）在真实的道路和车辆试验台上进行逼真的实验，以收集图像和无线数据集并评估研究。这些数据集对无线网络和计算机视觉研究社区都很感兴趣，并将向公众提供。

Emerging intelligent automobiles will be able to harness advance on-car sensors to support new applications such as pollution detection, road condition monitoring, and traffic control. All these applications require the ability to verify both the location and the time of a reading. This project involves the design of verification methods that make use of environment factors, such as the presence of light and shadows and the measured wireless signal strength, instead of conventional public key infrastructure-based methods, in order to verify when and where data was collected. This new environment-based paradigm is resilient against insider attacks, easier to deploy, and protects the individual car owner's privacy. This research will help in realizing applications arising from the increasing presence of smarter vehicles on our roads which can benefit the public's wellbeing. The project also incorporates outreach components for high school and college students through the organization of science competitions, national undergraduate workshops, and summer research camp activities. This project is the first effort to use the wireless communication and video recording abilities of modern automobiles to capture natural environment characteristics to securely verify spatial-temporal claims in a vehicular network setting. This is an interdisciplinary research effort combining wireless networking and computer vision to address vehicular network security. The main project goals are: (1) explore new vision analytic algorithms in order to identify the location and time images are captured by an automobile camera; (2) research new algorithms for identifying optimal roadside unit locations for location disambiguation to support wireless spatial-temporal verification; (3) develop new techniques for utilizing encounters with public vehicles for verifying spatial-temporal claims; (4) developing a fusion framework to combine wireless measurements, vehicular encounters, and visual images for spatial-temporal verification; and (5) perform realistic experiments on real roads and vehicular test bed to collect image and wireless datasets and evaluate the research. These datasets are of interest to both wireless networking and computer vision research communities, and will be made available to the public.