• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference >A Black Box Approach to Inferring, Characterizing, and Breaking Native Device Tracking Autonomy
【24h】

A Black Box Approach to Inferring, Characterizing, and Breaking Native Device Tracking Autonomy

机译：一种推断，表征和破坏本机追踪自主权的黑匣子方法

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Autonomous capabilities have emerged as a ubiquitous technology in cars, robots, drones and many other useful devices that are destined to transform our society. Many of the more advanced autonomous devices use computer vision to track and recognize objects, while others may use LIDAR or SONAR or other forms of radar. Since many of these devices are positioned to be disruptive technologies in our society, the fidelity of their abilities is paramount. In this paper, we introduce our black box approach, which can accurately infer, characterize, and break native device autonomy. We demonstrate this approach by using the tightly guarded autonomy code in the immensely popular computer vision driven autonomous DJI drones (i.e., ActiveTrack Mode) as the target native autonomy. We illustrate that this method allows us to quickly infer detailed information about the computer vision tracking algorithm, characterize the autonomous capability, and identify targets that defy these algorithms. We posit that this approach can be extended to other computer vision driven autonomous systems and is a necessary step in developing nondestructive privacy preserving mechanisms that foil the presumed tracking process.
机译：自主能力已成为汽车，机器人，无人机和许多注定要改变社会的许多其他有用设备的无处不在的技术。许多更先进的自主设备使用计算机愿景来跟踪和识别对象，而其他人可能会使用LIDAR或Sonar或其他形式的雷达。由于许多这些设备被定位为社会中的颠覆性技术，因此他们能力的保真度至关重要。在本文中，我们介绍了我们的黑匣子方法，可以准确地推断，表征和破坏本机设备自主权。我们通过使用大规模流行的计算机视觉驱动的自主DJI无人机（即，ActiveTack Mode）中的紧密保护的自主代码作为目标本机自主权来展示这种方法。我们说明该方法允许我们快速推断有关计算机视觉跟踪算法的详细信息，其特征是自主能力，并识别违抗这些算法的目标。我们对这种方法可以扩展到其他计算机视觉驱动的自治系统，并且是开发非破坏性隐私保留机制的必要步骤，这些机制融合了推定的跟踪过程。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号