1,459 research outputs found
Steganographer Identification
Conventional steganalysis detects the presence of steganography within single
objects. In the real-world, we may face a complex scenario that one or some of
multiple users called actors are guilty of using steganography, which is
typically defined as the Steganographer Identification Problem (SIP). One might
use the conventional steganalysis algorithms to separate stego objects from
cover objects and then identify the guilty actors. However, the guilty actors
may be lost due to a number of false alarms. To deal with the SIP, most of the
state-of-the-arts use unsupervised learning based approaches. In their
solutions, each actor holds multiple digital objects, from which a set of
feature vectors can be extracted. The well-defined distances between these
feature sets are determined to measure the similarity between the corresponding
actors. By applying clustering or outlier detection, the most suspicious
actor(s) will be judged as the steganographer(s). Though the SIP needs further
study, the existing works have good ability to identify the steganographer(s)
when non-adaptive steganographic embedding was applied. In this chapter, we
will present foundational concepts and review advanced methodologies in SIP.
This chapter is self-contained and intended as a tutorial introducing the SIP
in the context of media steganography.Comment: A tutorial with 30 page
Novel Framework for Hidden Data in the Image Page within Executable File Using Computation between Advanced Encryption Standard and Distortion Techniques
The hurried development of multimedia and internet allows for wide
distribution of digital media data. It becomes much easier to edit, modify and
duplicate digital information. In additional, digital document is also easy to
copy and distribute, therefore it may face many threats. It became necessary to
find an appropriate protection due to the significance, accuracy and
sensitivity of the information. Furthermore, there is no formal method to be
followed to discover a hidden data. In this paper, a new information hiding
framework is presented.The proposed framework aim is implementation of
framework computation between advance encryption standard (AES) and distortion
technique (DT) which embeds information in image page within executable file
(EXE file) to find a secure solution to cover file without change the size of
cover file. The framework includes two main functions; first is the hiding of
the information in the image page of EXE file, through the execution of four
process (specify the cover file, specify the information file, encryption of
the information, and hiding the information) and the second function is the
extraction of the hiding information through three process (specify the stego
file, extract the information, and decryption of the information).Comment: 6 Pages IEEE Format, International Journal of Computer Science and
Information Security, IJCSIS 2009, ISSN 1947 5500, Impact Factor 0.42
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