東華大學圖書館 |

Security and Privacy Solutions for Camera and Camera Based Authentication.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Security and Privacy Solutions for Camera and Camera Based Authentication./
作者:	Sun, Yuanyi.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	126 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Contained By:	Dissertations Abstracts International83-03B.
標題:	Software. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28841707
ISBN:	9798460448234

Security and Privacy Solutions for Camera and Camera Based Authentication.
Sun, Yuanyi.

Security and Privacy Solutions for Camera and Camera Based Authentication. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 126 p.

Source: Dissertations Abstracts International, Volume: 83-03, Section: B.

Thesis (Ph.D.)--The Pennsylvania State University, 2021.

This item must not be sold to any third party vendors.

The growing popularity of mobile devices with built-in cameras have brought up many opportunities and challenges. In particular, as camera capabilities continue to increase, one opportunity is to leverage such cameras as a second factor to support online user authentication under adversarial network environment. On the other hand, as capturing and recording with cameras have become a trivial job for ordinary people, who may further share their works with their friends or on the public platforms, privacy concerns arise because such digital works are often taken and shared without the consent of photographed people. It is a challenge for the photographing app to automatically learn the privacy preferences of people in the camera view and protect their privacy accordingly. Moreover, due to the COVID-19 epidemic, online video conferencing has become extremely popular throughout the world, with many schools, companies and government sectors using video conferencing applications (e.g., Zoom, Google Meet) in a daily basis. These applications also provide local or cloud recording services, which allow the replay or sharing of video conference recordings (VCRs) in a later time. Such convenience, however, can easily cause infringement of privacy as meeting participants' personally identifiable information (e.g., face, name, voice) may be exposed to the public without their awareness or unwillingly. This poses the challenge on the effective protection of privacy-sensitive users in VCRs. In this dissertation, in responding to the above opportunity and challenges, we propose three camera-based systems, PhotoAuth, iRyP and ZoomP3, respectively. Specifically, PhotoAuth is a camera-based two-factor authentication system against real-time phishing (RTP) attacks. The main idea is to request a user to take a photo of the web browser with the domain name in the address bar as the second authentication factor. The web server side extracts the domain name information based on Optical Character Recognition (OCR), and then determines if the user is visiting this website or a fake one, thus defeating the RTP attacks where an adversary must set up a fake website with a different domain. We prototyped PhotoAuth and evaluated its performance in various environments. The results showed that PhotoAuth is an effective technique with good scalability. We also showed that compared to other 2FA systems, PhotoAuth has several advantages, especially no special hardware or software support is needed on the client side except a phone, making it readily deployable. iRyP is a purely edge-based visual privacy-respecting system for mobile cameras. In order to meet the requirements of efficiency and usability, we propose to piggyback privacy policies in the advertising messages of Bluetooth Low Energy (BLE), which has been widely deployed in most mobile devices. As such, privacy policies of people in a photo view can be delivered timely and automatically. Moreover, we propose to use a perceptual hashing algorithm for fast face matching. To improve detection accuracy, we also design several new techniques for face-related image processing. We implement and evaluate a prototype system purely based on the Android platform. Our experiments show that iRyP can meet our design requirements and is practical and ready to use. In our research, we also propose the first privacy-preserving publishing system called (ZoomP3), which automatically processes video and audio information in VCRs for privacy protection. Besides leveraging and integrating multiple state-of-the-art computer vision and audio processing tools seamlessly into our system, a number of optimization algorithms are proposed to improve the scalability of the system, making it possible to protect the privacy of long video conferences. We have conducted various tests with short and long videos, and the results (with online demos) show that our system is suitable for large-scale use. It may be provided as an online service, e.g., by Zoom, or by large organizations such as universities, research institutes and government sectors.

ISBN: 9798460448234Subjects--Topical Terms:

619355
Software.
Subjects--Index Terms:

Video conferencing

Security and Privacy Solutions for Camera and Camera Based Authentication.
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500 $a Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
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502 $a Thesis (Ph.D.)--The Pennsylvania State University, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a The growing popularity of mobile devices with built-in cameras have brought up many opportunities and challenges. In particular, as camera capabilities continue to increase, one opportunity is to leverage such cameras as a second factor to support online user authentication under adversarial network environment. On the other hand, as capturing and recording with cameras have become a trivial job for ordinary people, who may further share their works with their friends or on the public platforms, privacy concerns arise because such digital works are often taken and shared without the consent of photographed people. It is a challenge for the photographing app to automatically learn the privacy preferences of people in the camera view and protect their privacy accordingly. Moreover, due to the COVID-19 epidemic, online video conferencing has become extremely popular throughout the world, with many schools, companies and government sectors using video conferencing applications (e.g., Zoom, Google Meet) in a daily basis. These applications also provide local or cloud recording services, which allow the replay or sharing of video conference recordings (VCRs) in a later time. Such convenience, however, can easily cause infringement of privacy as meeting participants' personally identifiable information (e.g., face, name, voice) may be exposed to the public without their awareness or unwillingly. This poses the challenge on the effective protection of privacy-sensitive users in VCRs. In this dissertation, in responding to the above opportunity and challenges, we propose three camera-based systems, PhotoAuth, iRyP and ZoomP3, respectively. Specifically, PhotoAuth is a camera-based two-factor authentication system against real-time phishing (RTP) attacks. The main idea is to request a user to take a photo of the web browser with the domain name in the address bar as the second authentication factor. The web server side extracts the domain name information based on Optical Character Recognition (OCR), and then determines if the user is visiting this website or a fake one, thus defeating the RTP attacks where an adversary must set up a fake website with a different domain. We prototyped PhotoAuth and evaluated its performance in various environments. The results showed that PhotoAuth is an effective technique with good scalability. We also showed that compared to other 2FA systems, PhotoAuth has several advantages, especially no special hardware or software support is needed on the client side except a phone, making it readily deployable. iRyP is a purely edge-based visual privacy-respecting system for mobile cameras. In order to meet the requirements of efficiency and usability, we propose to piggyback privacy policies in the advertising messages of Bluetooth Low Energy (BLE), which has been widely deployed in most mobile devices. As such, privacy policies of people in a photo view can be delivered timely and automatically. Moreover, we propose to use a perceptual hashing algorithm for fast face matching. To improve detection accuracy, we also design several new techniques for face-related image processing. We implement and evaluate a prototype system purely based on the Android platform. Our experiments show that iRyP can meet our design requirements and is practical and ready to use. In our research, we also propose the first privacy-preserving publishing system called (ZoomP3), which automatically processes video and audio information in VCRs for privacy protection. Besides leveraging and integrating multiple state-of-the-art computer vision and audio processing tools seamlessly into our system, a number of optimization algorithms are proposed to improve the scalability of the system, making it possible to protect the privacy of long video conferences. We have conducted various tests with short and long videos, and the results (with online demos) show that our system is suitable for large-scale use. It may be provided as an online service, e.g., by Zoom, or by large organizations such as universities, research institutes and government sectors.
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