BlindSpot: Creating Capture-Resistant Spaces

Patel, Shwetak; Summet, Jay; Truong, Khai N.

doi:10.1007/978-1-84882-301-3_11

Cited by 21 publications

(9 citation statements)

References 4 publications

(3 reference statements)

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“…These methods physically intervene camera devices to prevent the acquisition of an image by means of a specialised device that interferes with the camera optical lens. For instance, Patel et al (2009) developed the BlindSpot system. It locates any number of retro-reflective CCD or CMOS camera lenses around a protected area and, then, it directs a pulsing light at the detected lens, spoiling any images that cameras may record as Figure 2 shows.…”

Section: Protection Methodsmentioning

confidence: 99%

Visual privacy protection methods: A survey

Padilla-López

Chaaraoui

Flórez-Revuelta

2015

Expert Systems with Applications

172

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Recent advances in computer vision technologies have made possible the development of intelligent monitoring systems for video surveillance and ambientassisted living. By using this technology, these systems are able to automatically interpret visual data from the environment and perform tasks that would have been unthinkable years ago. These achievements represent a radical improvement but they also suppose a new threat to individual's privacy. The new capabilities of such systems give them the ability to collect and index a huge amount of private information about each individual. Next-generation systems have to solve this issue in order to obtain the users' acceptance. Therefore, there is a need for mechanisms or tools to protect and preserve people's privacy. This paper seeks to clarify how privacy can be protected in imagery data, so as a main contribution a comprehensive classification of the protection methods for visual privacy as well as an up-to-date review of them are provided. A survey of the existing privacy-aware intelligent monitoring systems and a valuable discussion of important aspects of visual privacy are also provided.

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Section: Protection Methodsmentioning

confidence: 99%

Visual privacy protection methods: A survey

Padilla-López

Chaaraoui

Flórez-Revuelta

2015

Expert Systems with Applications

172

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“…Some systems proposed in the literature use supporting intervention or tokens to protect people's privacy in the video. Patel et al have proposed an unusual approach, dubbed an "anti-paparazzi" device, to create a privacy-protection solution where no control can be exerted over the use of the images or video once recorded [26]. In their detection system, a bright infra-red source is located near a camera.…”

Section: Intervention Tokens and Privacy Policiesmentioning

confidence: 98%

The privacy challenges of in-depth video analytics

Piatrik

Fernández

Izquierdo

2012

2012 IEEE 14th International Workshop on Multimedia Signal Processing (MMSP)

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The increasing need for both automated and privacy-respecting CCTV systems adds many challenges to the tasks of Video Analytics. The growing capabilities of automated surveillance systems lead to the automatic extraction and processing of complex and potentially personal data related to individuals who may not even be aware of it. This paper discusses the issues related to the processing of potentially sensitive information extracted from various computer vision algorithms and techniques such as person tracking, soft biometrics, behaviour analysis or multi-modal person identification, and delivers insights regarding technical solutions and guidelines for achieving a higher level of privacy compliance.

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“…Our work can support all of these prior special-purpose policies, but moves beyond them in (1) providing a dynamically extensible framework that can support any policy, (2) allowing any real-world object to specify its policy by a variety (or combination) of technological mechanisms, and (3) tackling the challenge of policy authenticity by introducing passports. The above-mentioned designs, like ours, rely on compliant recording devices or vendors; other systems aim to prevent recording by uncooperative devices, e.g., by flashing directed light at cameras [32]. Recent work studied bystander reactions to augmented reality devices and surveyed design axes for privacy-mediation approaches [11].…”

Section: Additional Related Workmentioning

confidence: 99%

World-Driven Access Control for Continuous Sensing

Roesner

Molnár

Moshchuk

et al. 2014

Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security

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Modern applications increasingly rely on continuous monitoring of video, audio, or other sensor data to provide their functionality, particularly in platforms such as the Microsoft Kinect and Google Glass. Continuous sensing by untrusted applications poses significant privacy challenges for both device users and bystanders. Even honest users will struggle to manage application permissions using existing approaches.We propose a general, extensible framework for controlling access to sensor data on multi-application continuous sensing platforms. Our approach, world-driven access control, allows real-world objects to explicitly specify access policies. This approach relieves the user's permission management burden while mediating access at the granularity of objects rather than full sensor streams. A trusted policy module on the platform senses policies in the world and modifies applications' "views" accordingly. For example, world-driven access control allows the system to automatically stop recording in bathrooms or remove bystanders from video frames, without the user prompted to specify or activate such policies. To convey and authenticate policies, we introduce passports, a new kind of certificate that includes both a policy and optionally the code for recognizing a real-world object.We implement a prototype system and use it to study the feasibility of world-driven access control in practice. Our evaluation suggests that world-driven access control can effectively reduce the user's permission management burden in emerging continuous sensing systems. Our investigation also surfaces key challenges for future access control mechanisms for continuous sensing applications. Figure 1: Sensor Privacy Concerns. Camera restrictionsare common in sensitive locations like locker rooms, where both device users' and bystanders' privacy are at risk from untrusted applications. Continuous sensing platforms like Google Glass will make it harder for honest users to mitigate such risks by managing applications' permissions. World-driven access control allows real-world objects to push policies to devices.

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BlindSpot: Creating Capture-Resistant Spaces

Cited by 21 publications

References 4 publications

Visual privacy protection methods: A survey

Visual privacy protection methods: A survey

The privacy challenges of in-depth video analytics

World-Driven Access Control for Continuous Sensing

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