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EURASIP Journal on Information Security - An Open Access Journal
Special Issue on
Robust Perceptual Hashing of Multimedia Content
Call for Papers
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New possibilities of digital imaging and audio open wide
prospects in modern imaging science, content management and secure
communications. However, despite the obvious advantages of modern
digital
technologies and their ongoing progress, these developments carry
inherent
risks, such as copyright violation, unauthorized prohibited usage and
distribution of digital media, high fidelity efficient counterfeiting
of
digital and analog content as well as brand products. An urgent need
for
reliable document, product and person identification also calls for
emerging
necessity in robust and secure techniques, capable of withstanding
various
attacks, and at the same time preserving privacy. On the other hand,
the issue
of security is not necessarily emphasized in several other relevant
applications, such as content indexing and retrieval, but such tasks
also
require reliable and computationally efficient techniques for semantic
content
management.
Robust
perceptual hashing (also termed as
fingerprinting in some contexts) methods have been
recently
proposed as primitives to overcome the above problems and have
constituted the
core of a challenging and dynamically developing research area.
Although the robustness/invariance aspects of multimedia hashing have
received a lot of attention especially in computer vision, the issue of
security still remains to be an open and little-studied problem. New
information-theoretic and detection-theoretic approaches to secure
hashing, as well as carefully designed attacks, should be proposed and
investigated. This aspect will potentially have a great impact on
security applications, such as content, object, person authentication
and identification, tamper evidence, synchronization, forensic analysis
and brand protection.
The main goal of this special issue is to provide original
contributions to the theoretic and security aspects of
Robust
Perceptual Hashing and relevant
applications. Some of the related research topics for the submission
include, but are not limited to:
- Information-theoretic and detection-theoretic aspects of robust
perceptual hashing
- Performance, complexity and security analysis of robust perceptual
hashing
- Practical robust and secure perceptual hashing algorithms for images,
video, audio and text data
- Robust perceptual hashing in key-dependent transform and encrypted
domains
- Robust perceptual hashing applications: content, object, person
authentication and identification, biometrics, tamper proofing,
synchronization, forensic analysis, brand protection
- Attacks against robust perceptual hashing
Following the policy of the EURASIP JIS targeting achieving the highest
quality standards with regard to the experimental section of published
papers and supporting the principle of scientific reproducibility of
the obtained experimental results, the authors are highly encouraged to
share the exploited data sets used in the experimental part of papers
as well as the source code used to produce the main experimental
results with reviewers and users under the conditions defined by the
JIS aims and scope.
Authors should follow the EURASIP JIS manuscript format described at
http://www.hindawi.com/journals/is/
Prospective authors should submit an electronic copy of their complete
manuscript through the EURASIP JIS’s Manuscript Tracking System at
http://www.hindawi.com/mts/
, according to the following tentative timetable:
Manuscripts due: May 1, 2007
Acceptance notification: September 1, 2007
Final manuscript due: November 1, 2007
Publication date: 4^th Quarter, 2007
*Guest Editors*:
*Kivanc Mihcak*, Electrical and Electronic
Engineering Department, Bogazici University, Bebek, 34342, Istanbul,
Turkey;
kivanc.mihcak@boun.edu.tr
*Oleksiy Koval*, Stochastic Image Processing Group,
Department of Computer Sciences, CUI-University of Geneva, 24 rue
General-Dufour, 1211 Geneva, Switzerland;
koval@cui.unige.ch
*Sviatoslav
Voloshynovskiy*, Stochastic Image
Processing Group, Department of Computer Sciences, CUI-University of
Geneva, 24 rue General-Dufour, 1211 Geneva, Switzerland;
svolos@cui.unige.ch
