775 research outputs found
Using Facebook for Image Steganography
Because Facebook is available on hundreds of millions of desktop and mobile
computing platforms around the world and because it is available on many
different kinds of platforms (from desktops and laptops running Windows, Unix,
or OS X to hand held devices running iOS, Android, or Windows Phone), it would
seem to be the perfect place to conduct steganography. On Facebook, information
hidden in image files will be further obscured within the millions of pictures
and other images posted and transmitted daily. Facebook is known to alter and
compress uploaded images so they use minimum space and bandwidth when displayed
on Facebook pages. The compression process generally disrupts attempts to use
Facebook for image steganography. This paper explores a method to minimize the
disruption so JPEG images can be used as steganography carriers on Facebook.Comment: 6 pages, 4 figures, 2 tables. Accepted to Fourth International
Workshop on Cyber Crime (IWCC 2015), co-located with 10th International
Conference on Availability, Reliability and Security (ARES 2015), Toulouse,
France, 24-28 August 201
Blindspot: Indistinguishable Anonymous Communications
Communication anonymity is a key requirement for individuals under targeted
surveillance. Practical anonymous communications also require
indistinguishability - an adversary should be unable to distinguish between
anonymised and non-anonymised traffic for a given user. We propose Blindspot, a
design for high-latency anonymous communications that offers
indistinguishability and unobservability under a (qualified) global active
adversary. Blindspot creates anonymous routes between sender-receiver pairs by
subliminally encoding messages within the pre-existing communication behaviour
of users within a social network. Specifically, the organic image sharing
behaviour of users. Thus channel bandwidth depends on the intensity of image
sharing behaviour of users along a route. A major challenge we successfully
overcome is that routing must be accomplished in the face of significant
restrictions - channel bandwidth is stochastic. We show that conventional
social network routing strategies do not work. To solve this problem, we
propose a novel routing algorithm. We evaluate Blindspot using a real-world
dataset. We find that it delivers reasonable results for applications requiring
low-volume unobservable communication.Comment: 13 Page
Unified Description for Network Information Hiding Methods
Until now hiding methods in network steganography have been described in
arbitrary ways, making them difficult to compare. For instance, some
publications describe classical channel characteristics, such as robustness and
bandwidth, while others describe the embedding of hidden information. We
introduce the first unified description of hiding methods in network
steganography. Our description method is based on a comprehensive analysis of
the existing publications in the domain. When our description method is applied
by the research community, future publications will be easier to categorize,
compare and extend. Our method can also serve as a basis to evaluate the
novelty of hiding methods proposed in the future.Comment: 24 pages, 7 figures, 1 table; currently under revie
Performance Analysis on Text Steganalysis Method Using A Computational Intelligence Approach
In this paper, a critical view of the utilization ofcomputational intelligence approach from the text steganalysisperspective is presented. This paper proposes a formalization ofgenetic algorithm method in order to detect hidden message on ananalyzed text. Five metric parameters such as running time, fitnessvalue, average mean probability, variance probability, and standarddeviation probability were used to measure the detection performancebetween statistical methods and genetic algorithm methods.Experiments conducted using both methods showed that geneticalgorithm method performs much better than statistical method,especially in detecting short analyzed texts. Thus, the findings showedthat the genetic algorithm method on analyzed stego text is verypromising. For future work, several significant factors such as datasetenvironment, searching process and types of fitness values throughother intelligent methods of computational intelligence should beinvestigated
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