机器人研究人员开发了一种设计相机的新方法，他们说这有助于保护智能家居设备和物联网技术收集的图像和数据。 与保护隐私的相机相比，普通相机看到的是什么。 图片：悉尼大学和昆士兰科技大学从机器人吸尘器、智能冰箱到婴儿监护仪和无人机，越来越多的智能设备被欢迎进入我们的家庭和工作场所，它们使用视觉拍摄周围环境，在这个过程中拍摄我们生活的视频和图像。 为了恢复隐私，悉尼大学澳大利亚机器人中心和昆士兰科技大学量子技术机器人中心的研究人员创造了一种新的方法来设计相机，在视觉信息数字化之前对其进行处理和扰乱，使其变得模糊到匿名的地步。 被称为视觉系统的设备，如自动吸尘器，构成了“物联网”的一部分，即连接到互联网的智能系统。 他们可能面临被不良行为者入侵或因人为错误而丢失的风险，他们的图像和视频也有被第三方窃取的风险，有时是出于恶意。 作为“指纹”，扭曲的图像仍然可以被机器人用来完成任务，但不能提供全面的视觉表现，从而损害隐私。 adamtaras说：“智能设备正在改变我们的工作和生活方式，但它们不应该损害我们的隐私，成为监视工具。”他完成了这项研究，这是他的荣誉论文的一部分。 “当我们想到‘视觉’时，我们会把它想象成一张照片，而这些设备中的许多都不需要像人类那样对场景进行视觉访问。 他说：“他们使用其他视觉信号，如颜色和模式识别，来测量完成任务所需的范围非常窄。”。 普通相机看到的与保护隐私的相机看到的研究人员已经能够将计算机内部通常发生的处理过程分割到相机的光学器件和模拟电子器件中，这是攻击者无法触及的。 澳大利亚机器人与数字科学倡议中心taras的主管don dansereau博士说：“这是与之前的工作的关键区别，之前的工作混淆了相机计算机内的图像，使图像容易受到攻击。”。 “我们超越了电子产品本身，实现了更高级别的保护。 “研究人员试图破解他们的方法，但无法以任何可识别的格式重建图像。 他们已经向整个研究界开放了这项任务，挑战其他人破解他们的方法。 塔拉斯说：“如果这些图像被第三方访问，他们将无法对其进行大量制作，隐私也将得到保护。”。 dansereau博士表示，随着如今越来越多的设备配备内置摄像头，以及在不久的将来可能增加的新技术，如包裹无人机，隐私越来越受到关注。无人机可以进入居民区送货。 “你不希望你的机器人吸尘器在家里拍摄的图像泄露在暗网上，也不希望送货无人机在你的后院绘制地图。 dansereau博士说：“允许链接到网络的服务获取并保留这些信息风险太大了。”。 这种方法还可以用于制造在仓库、医院、工厂、学校和机场等关注隐私和安全的地方工作的设备。 研究人员希望下一步建立物理相机原型，以在实践中演示这种方法。 “目前的机器人视觉技术往往忽视了终端用户的合法隐私问题。 这是一种短视的策略，会减缓甚至阻止机器人技术在许多具有社会和经济重要性的应用中的应用。 qcr副主任niko suenderhauf教授表示：“我们的新传感器设计非常重视隐私，我希望看到它被工业界所接受，并在许多应用中得到应用。”。 qcr杰出荣誉退休教授兼兼职教授petercoke教授也为该项目提供建议，他说：“相机相当于机器人的眼睛，对于理解世界、了解什么是什么以及在哪里是非常宝贵的。 我们不希望这些相机的照片离开机器人的身体，无意中透露出机器人环境中人或物的私人或亲密细节。 《负责任技术杂志》发表了这项研究，题为《值得信赖的自主系统的固有隐私保护愿景：需求和解决方案》。 声明作者声明没有相互竞争的利益。robotic researchers have developed a new approach to designing cameras, which they say could help protect the images and data collected by smart home devices and internet-of-things technology.what a normal camera sees compared with what the privacy preserving camera sees. image: university of sydney and queensland university of technologyfrom robotic vacuum cleaners and smart fridges to baby monitors and delivery drones, the smart devices being increasingly welcomed into our homes and workplaces use vision to take in their surroundings, taking videos and images of our lives in the process. in a bid to restore privacy, researchers at the australian centre for robotics at the university of sydney and the qut centre for robotics (qcr) at queensland university of technology have created a new approach to designing cameras that process and scramble visual information before it is digitised so that it becomes obscured to the point of anonymity. known as sighted systems, devices like autonomous vacuum cleaners form part of the “internet-of-things” – smart systems that connect to the internet. they can be at risk of being hacked by bad actors or lost through human error, their images and videos at risk of being stolen by third parties, sometimes with malicious intent. acting as a “fingerprint,” the distorted images can still be used by robots to complete their tasks but do not provide a comprehensive visual representation that compromises privacy. “smart devices are changing the way we work and live our lives, but they shouldn’t compromise our privacy and become surveillance tools,” said adam taras, who completed the research as part of his honours thesis. “when we think of ‘vision’ we think of it like a photograph, whereas many of these devices don’t require the same type of visual access to a scene as humans do. they have a very narrow scope in terms of what they need to measure to complete a task, using other visual signals, such as colour and pattern recognition,” he said. what a normal camera sees vs what the privacy preserving camera seesthe researchers have been able to segment the processing that normally happens inside a computer within the optics and analogue electronics of the camera, which exists beyond the reach of attackers. “this is the key distinguishing point from prior work which obfuscated the images inside the camera’s computer – leaving the images open to attack,” said dr don dansereau, taras’ supervisor at the australian centre for robotics and digital sciences initiative. ”we go one level beyond to the electronics themselves, enabling a greater level of protection.” the researchers tried to hack their approach but were unable to reconstruct the images in any recognisable format. they have opened this task to the research community at large, challenging others to hack their method. “if these images were to be accessed by a third party, they would not be able to make much of them, and privacy would be preserved,” said taras. dr dansereau said privacy was increasingly becoming a concern as more devices today come with built-in cameras, and with the possible increase in new technologies in the near future like parcel drones, which travel into residential areas to make deliveries. “you wouldn’t want images taken inside your home by your robot vacuum cleaner leaked on the dark web, nor would you want a delivery drone to map out your backyard. it is too risky to allow services linked to the web to capture and hold onto this information,” said dr dansereau. the approach could also be used to make devices that work in places where privacy and security are a concern, such as warehouses, hospitals, factories, schools and airports. the researchers hope to next build physical camera prototypes to demonstrate the approach in practice. “current robotic vision technology tends to ignore the legitimate privacy concerns of end-users. this is a short-sighted strategy that slows down or even prevents the adoption of robotics in many applications of societal and economic importance. our new sensor design takes privacy very seriously, and i hope to see it taken up by industry and used in many applications,” said professor niko suenderhauf, deputy director of the qcr, who advised on the project. professor peter corke, distinguished professor emeritus and adjunct professor at the qcr who also advised on the project said: “cameras are the robot equivalent of a persons eyes, invaluable for understanding the world, knowing what is what and where it is. what we don’t want is the pictures from those cameras to leave the robot’s body, to inadvertently reveal private or intimate details about people or things in the robot’s environment.” research the research, inherently privacy-preserving vision for trustworthy autonomous systems: needs and solutions, was published by the journal of responsible technology.declarationthe authors declare no competing interests.本文来源： 新的保护隐私的机器人相机掩盖了人类无法识别的图像
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