41 research outputs found
Implementation of the DSSS method in watermarking digital audio objects
The paper presents the results of implementation in the Matlab environment for watermarking
embedder and extractor based on the Direct Sequence Spread Spectrum (DSSS). A block
diagram of watermarking system, an analysis of watermarked signal reproduced as well as
watermarking system robustness to degrading factors: lossy compression, signal-to-noise ratio
(SNR) as well as a change in sampling frequency, were shown
Acoustic transmission of metadata in audio files using Sonic Quick Response Codes (SQRC)
With the advent of high-resolution recording and playback systems, a proportion of the ultrasonic frequency spectrum can potentially be utilized as a carrier for imperceptible data, which can be used to trigger events or to hold metadata in the form of, for example, an ISRC (International Standard Recording Code), a website URL or audio track liner notes. The Sonic Quick Response Code (SQRC) algorithm was previously proposed as a method for encoding inaudible acoustic metadata within a 96 kHz audio file in the 30-35 kHz range
The Automation of the Extraction of Evidence masked by Steganographic Techniques in WAV and MP3 Audio Files
Antiforensics techniques and particularly steganography and cryptography have
become increasingly pressing issues that affect the current digital forensics
practice, both techniques are widely researched and developed as considered in
the heart of the modern digital era but remain double edged swords standing
between the privacy conscious and the criminally malicious, dependent on the
severity of the methods deployed. This paper advances the automation of hidden
evidence extraction in the context of audio files enabling the correlation
between unprocessed evidence artefacts and extreme Steganographic and
Cryptographic techniques using the Least Significant Bits extraction method
(LSB). The research generates an in-depth review of current digital forensic
toolkit and systems and formally address their capabilities in handling
steganography-related cases, we opted for experimental research methodology in
the form of quantitative analysis of the efficiency of detecting and extraction
of hidden artefacts in WAV and MP3 audio files by comparing standard industry
software. This work establishes an environment for the practical implementation
and testing of the proposed approach and the new toolkit for extracting
evidence hidden by Cryptographic and Steganographic techniques during forensics
investigations. The proposed multi-approach automation demonstrated a huge
positive impact in terms of efficiency and accuracy and notably on large audio
files (MP3 and WAV) which the forensics analysis is time-consuming and requires
significant computational resources and memory. However, the proposed
automation may occasionally produce false positives (detecting steganography
where none exists) or false negatives (failing to detect steganography that is
present) but overall achieve a balance between detecting hidden data accurately
along with minimising the false alarms.Comment: Wires Forensics Sciences Under Revie
Copyright protection of scalar and multimedia sensor network data using digital watermarking
This thesis records the research on watermarking techniques to address the issue of copyright protection of the scalar data in WSNs and image data in WMSNs, in order to ensure that the proprietary information remains safe between the sensor nodes in both. The first objective is to develop LKR watermarking technique for the copyright protection of scalar data in WSNs. The second objective is to develop GPKR watermarking technique for copyright protection of image data in WMSN
Spread spectrum-based video watermarking algorithms for copyright protection
Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can
now benefit from hardware and software which was considered state-of-the-art several years
ago. The advantages offered by the digital technologies are major but the same digital
technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly
possible and relatively easy, in spite of various forms of protection, but due to the analogue
environment, the subsequent copies had an inherent loss in quality. This was a natural way of
limiting the multiple copying of a video material. With digital technology, this barrier
disappears, being possible to make as many copies as desired, without any loss in quality
whatsoever. Digital watermarking is one of the best available tools for fighting this threat.
The aim of the present work was to develop a digital watermarking system compliant with the
recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark
can be inserted in either spatial domain or transform domain, this aspect was investigated and
led to the conclusion that wavelet transform is one of the best solutions available. Since
watermarking is not an easy task, especially considering the robustness under various attacks
several techniques were employed in order to increase the capacity/robustness of the system:
spread-spectrum and modulation techniques to cast the watermark, powerful error correction
to protect the mark, human visual models to insert a robust mark and to ensure its invisibility.
The combination of these methods led to a major improvement, but yet the system wasn't
robust to several important geometrical attacks. In order to achieve this last milestone, the
system uses two distinct watermarks: a spatial domain reference watermark and the main
watermark embedded in the wavelet domain. By using this reference watermark and techniques
specific to image registration, the system is able to determine the parameters of the attack and
revert it. Once the attack was reverted, the main watermark is recovered. The final result is a
high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen
Improved steganalysis technique based on least significant bit using artificial neural network for MP3 files
MP3 files are one of the most widely used digital audio formats that provide a high compression ratio with reliable quality. Their widespread use has resulted in MP3 audio files becoming excellent covers to carry hidden information in audio steganography on the Internet. Emerging interest in uncovering such hidden information has opened up a field of research called steganalysis that looked at the detection of hidden messages in a specific media. Unfortunately, the detection accuracy in steganalysis is affected by bit rates, sampling rate of the data type, compression rates, file track size and standard, as well as benchmark dataset of the MP3 files. This thesis thus proposed an effective technique to steganalysis of MP3 audio files by deriving a combination of features from MP3 file properties. Several trials were run in selecting relevant features of MP3 files like the total harmony distortion, power spectrum density, and peak signal-to-noise ratio (PSNR) for investigating the correlation between different channels of MP3 signals. The least significant bit (LSB) technique was used in the detection of embedded secret files in stego-objects. This involved reading the stego-objects for statistical evaluation for possible points of secret messages and classifying these points into either high or low tendencies for containing secret messages. Feed Forward Neural Network with 3 layers and traingdx function with an activation function for each layer were also used. The network vector contains information about all features, and is used to create a network for the given learning process. Finally, an evaluation process involving the ANN test that compared the results with previous techniques, was performed. A 97.92% accuracy rate was recorded when detecting MP3 files under 96 kbps compression. These experimental results showed that the proposed approach was effective in detecting embedded information in MP3 files. It demonstrated significant improvement in detection accuracy at low embedding rates compared with previous work