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short-paper

Image Segmentation Based Visual Security Evaluation

Authors:

Christof Kauba,

Andreas UhlAuthors Info & Claims

IH&MMSec '16: Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia Security

Pages 175 - 180

https://doi.org/10.1145/2909827.2930806

Published: 20 June 2016 Publication History

Abstract

In this paper we present a metric for visual security evaluation of encrypted images, also known as visual security metric. Such a metric should be able to assess whether an image encryption method is secure or not. In order to consider intelligibility of objects in encrypted images our metric is based on image segmentation and applying a measure designed to evaluate the segmentation result. The visual security metrics' performance is evaluated using a selective encryption approach and compared to some general image quality metrics like PSNR, metrics suggested for encrypted images like Irregular Deviation and two metrics specifically designed for visual security evaluation. Our visual security metric performs better than all of the other tested metrics on the dataset and encryption algorithm we used during our experiments in terms of different correlation measures.

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Cited By

Wen WHuang MZhang YFang YZuo Y(2023)Visual Security Index Combining CNN and Filter for Perceptually Encrypted Light Field ImagesACM Transactions on Multimedia Computing, Communications, and Applications10.1145/361292420:1(1-15)Online publication date: 3-Aug-2023
https://dl.acm.org/doi/10.1145/3612924
Gan ZZhang YHuang ZChai XSong YHe X(2023)Visual security index of selective encrypted images based on multi-directional structure and content-aware featuresJournal of Electronic Imaging10.1117/1.JEI.32.4.04301832:04Online publication date: 1-Jul-2023
https://doi.org/10.1117/1.JEI.32.4.043018
Yang YXiang TLiu HLiao X(2021)Convolutional Neural Network for Visual Security EvaluationIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2020.303685431:8(3293-3307)Online publication date: Aug-2021
https://doi.org/10.1109/TCSVT.2020.3036854
Show More Cited By

Index Terms

Image Segmentation Based Visual Security Evaluation
1. Computing methodologies
  1. Computer graphics
    1. Image manipulation
2. Security and privacy
  1. Cryptography

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Information & Contributors

Information

Published In

cover image ACM Conferences

IH&MMSec '16: Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia Security

June 2016

200 pages

ISBN:9781450342902

DOI:10.1145/2909827

General Chairs:
Fernando Pérez-González
University of Vigo, Spain
,
Patrick Bas
CNRS, University of Lille, France
,
Program Chairs:
Tanya Ignatenko
Eindhoven University of Technology, The Netherlands
,
François Cayre
Grenoble INP, University of Grenoble Alpes, France

Copyright © 2016 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGMM: ACM Special Interest Group on Multimedia

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 June 2016

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Short-paper

Funding Sources

Austrian Science Fund

Conference

IH&MMSec '16

Sponsor:

SIGMM

IH&MMSec '16: ACM Information Hiding and Multimedia Security Workshop

June 20 - 22, 2016

Galicia, Vigo, Spain

Acceptance Rates

IH&MMSec '16 Paper Acceptance Rate 21 of 61 submissions, 34%;

Overall Acceptance Rate 128 of 318 submissions, 40%

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Citations

Cited By

Wen WHuang MZhang YFang YZuo Y(2023)Visual Security Index Combining CNN and Filter for Perceptually Encrypted Light Field ImagesACM Transactions on Multimedia Computing, Communications, and Applications10.1145/361292420:1(1-15)Online publication date: 3-Aug-2023
https://dl.acm.org/doi/10.1145/3612924
Gan ZZhang YHuang ZChai XSong YHe X(2023)Visual security index of selective encrypted images based on multi-directional structure and content-aware featuresJournal of Electronic Imaging10.1117/1.JEI.32.4.04301832:04Online publication date: 1-Jul-2023
https://doi.org/10.1117/1.JEI.32.4.043018
Yang YXiang TLiu HLiao X(2021)Convolutional Neural Network for Visual Security EvaluationIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2020.303685431:8(3293-3307)Online publication date: Aug-2021
https://doi.org/10.1109/TCSVT.2020.3036854
Rieger MHammerle-Uhl JUhl A(2021)Security Assessment of Selectively Encrypted Visual Data: Iris Recognition on Protected Samples2021 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP42928.2021.9506294(3008-3012)Online publication date: 19-Sep-2021
https://doi.org/10.1109/ICIP42928.2021.9506294
Hofbauer HAutrusseau FUhl A(2021)To recognize or not to recognize – A database of encrypted images with subjective recognition ground truthInformation Sciences10.1016/j.ins.2020.11.047551(128-145)Online publication date: Apr-2021
https://doi.org/10.1016/j.ins.2020.11.047
Xiang TYang YLiu HGuo S(2020)Visual Security Evaluation of Perceptually Encrypted Images Based on Image ImportanceIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2019.295529830:11(4129-4142)Online publication date: Nov-2020
https://doi.org/10.1109/TCSVT.2019.2955298
Rieger MHammerle-Uhl JUhl A(2020)Security Assessment of Partially Encrypted Visual Data: Using Iris Recognition as Generic Measure2020 8th International Workshop on Biometrics and Forensics (IWBF)10.1109/IWBF49977.2020.9107967(1-6)Online publication date: Apr-2020
https://doi.org/10.1109/IWBF49977.2020.9107967

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