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AuthPaper Hi-Q Scanner app for iPhone and iPad


4.4 ( 9984 ratings )
Education
Developer: Chak Man Li
Free
Current version: 3.0, last update: 6 years ago
First release : 10 Jul 2015
App size: 14.2 Mb

This scanner application verifies issuer of a document created in the AuthPaper project by scanning an Authenticated QR code embedded on the document.
This scanner can also scan and create normal QR codes,
AuthPaper, or Authenticated Papers, is a research project by MobiTeC, The Chinese University of Hong Kong.
AuthPaper provides an offline, cost-effective, secure solution for authenticating paper-based documents/credentials using off-the-shelf handheld devices such as smartphones and tablets.
The key idea is to extend existing 2D barcodes, e.g. the QR-code, to carry a large amount of self-describing, and most importantly, authenticated data of all types containing text, image as well as other binary ones. By embedding the Authenticated 2D Barcode as an integral part of a paper-based document, the authenticity of the document can be readily verified by comparing its content with the corresponding digitally-signed content contained in the Authenticated 2D Barcode.
Encrypted message and image can also be embedded into the Authenticated 2D Barcode.
Details can be found in http://mobitec.ie.cuhk.edu.hk/authpaper/ and http://www.authpaper.net.
The code verification process does not need the access of the Internet.
The only reason of declaring the Internet permission is to collect usage statistics.
At the first time you open the App, we will get your email address and hardware details for statistics purpose.
We will also collect some information anonymously on each successful scanning (scanning time, size of scanned QR code, number of frames taken, etc.) for usage statistics purpose, but the privacy information like QR code contents, camera images and user information are not collected.
You may also disable the data collection in the setting page.
The AuthPaper creation service is available on https://www.authpaper.net.
If you find any problem, please inform us.
This research is supported in part by grants from the Innovation and Technology Fund (ITF) of the Hong Kong SAR Government (Project no. ITS/300/13) and the Knowledge Transfer Fund at CUHK (Project no. TBF14ENG004).