Data Mining Practical Machine Learning Tools and Techniques

Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

Digital Watermarking

National Institute of Standards and Technology における超伝導研究及び生活

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

One of the main problems, which darkens the future of digital watermarking technologies, is the lack of detailed evaluation of existing marking schemes. This lack of benchmarking of current algorithms is blatant and confuses rights holders as well as software and hardware manufacturers and prevents them from using the solution appropriate to their needs. Indeed basing long-lived protection schemes on badly tested watermarking technology does not make sense. In this paper we will present the architecture of a public automated evaluation service we have developed for still images, sound and video. We will detail and justify our choice of evaluation profiles, that is the series of tests applied to different types of wa-termarking schemes. These evaluation profiles allow us to measure the reliability of a marking scheme to different levels from low to very high. Beside the known StirMark transformations, we will also detail new tests that will be included in this platform. One of them is intended to measure the real size of the key space. Indeed, if one is not careful, two different watermarking keys may produce interfering watermarks and as a consequence the actual space of keys is much smaller than it appears. Another set of tests is related to audio data and addresses the usual equalisation and normalisation but also time stretching, pitch shifting. Finally we propose a set of tests for fingerprinting applications. This includes: averaging of copies with different fingerprint, random ex-change of part between different copies and comparison between copies with selection of most/less frequently used position differences.

Public automated web-based evaluation service for watermarking schemes: StirMark benchmark

Media forensics tries to determine the originating device of a signal. We apply this paradigm to microphone forensics, determining the microphone model used to record a given audio sample. Our approach is to extract a Fourier coefficient histogram of near-silence segments of the recording as the feature vector and to use machine learning techniques for the classification. Our test goals are to determine whether attempting microphone forensics is indeed a sensible approach and which one of the six different classification techniques tested is the most suitable one for that task. The experimental results, achieved using two different FFT window sizes (256 and 2048 frequency coefficients) and nine different thresholds for near-silence detection, show a high accuracy of up to 93.5% correct classifications for the case of 2048 frequency coefficients in a test set of seven microphones classified with linear logistic regression models. This positive tendency motivates further experiments with larger test sets and further studies for microphone identification.

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Microphone Classification Using Fourier Coefficients

Digital watermarking is the enabling technology to prove ownership on copyrighted material, detect originators of illegally made copies, monitor the usage of the copyrighted multimedia data, and analyze the spread spectrum of the data over networks and servers. Embedding of unique customer identification as a watermark into data is called fingerprinting to identify illegal copies of documents. Basically, watermarks embedded into multimedia data for enforcing copyrights must uniquely identify the data and must be difficult to remove, even after various media transformation processes. Digital fingerprinting raises the additional problem that we produce different copies for each customer. Attackers can compare several fingerprinted copies to find and destroy the embedded identification string by altering the data in those places where a difference was detected. In our paper we present a technology for combining a collusion-secure fingerprinting scheme based on finite geometries and a watermarking mechanism with special marking points for digital images. The only marking positions the pirates cannot detect are those positions which contain the same letter in all the compared documents, called intersection of different fingerprints. The proposed technology for a maximal number d of pirates, puts enough information in the intersection of up to d fingerprints to uniquely identify all the pirates. © 2000 SPIE and IS&T.

Combining digital watermarks and collusion secure fingerprints for digital images

Steganography and steganalysis in VoIP applications are important research topics as speech data is an appropriate
cover to hide messages or comprehensive documents. In our paper we introduce a Mel-cepstrum based
analysis known from speaker and speech recognition to perform a detection of embedded hidden messages. In
particular we combine known and established audio steganalysis features with the features derived from Melcepstrum
based analysis for an investigation on the improvement of the detection performance. Our main focus
considers the application environment of VoIP-steganography scenarios.
The evaluation of the enhanced feature space is performed for classical steganographic as well as for watermarking
algorithms. With this strategy we show how general forensic approaches can detect information hiding
techniques in the field of hidden communication as well as for DRM applications. For the later the detection of
the presence of a potential watermark in a specific feature space can lead to new attacks or to a better design of
the watermarking pattern. Following that the usefulness of Mel-cepstrum domain based features for detection is
discussed in detail.

/pdf/mel-cepstrum-based-steganalysis-for-voip-steganography-szy0o6lubj.pdf

Mel-cepstrum-based steganalysis for VoIP steganography

Based on the knowledge and experiences from existing image steganalysis techniques, the overall objective of the paper is to evaluate existing audio steganography with a special focus on attacks in ad-hoc end-to-end media communications on the example of Voice over IP (VoIP) scenarios. One aspect is to understand operational requirements of recent steganographic techniques for VoIP applications. The other aspect is to elaborate possible steganalysis approaches applied to speech data. In particular we have examined existing VoIP applications with respect to their extensibility to steganographic algorithms. We have also paid attention to the part of steganalysis in PCM audio data which allows us to detect hidden communication while a running VoIP communication with the usage of the PCM codec. In our impelementation we use Jori's Voice over IP library by Jori Liesenborgs (JVOIPLIB) that provides primitives for a voice over IP communication. Finally we show first results of our prototypic implementation which extents the common VoIP scenario by the new feature of steganography. We also show the results for our PCM steganalyzer framework that is able to detect this kind of hidden communication by using a set of 13 first and second order statistics.

Jana Dittmann

Papers

Public automated web-based evaluation service for watermarking schemes: StirMark benchmark

Microphone Classification Using Fourier Coefficients

Combining digital watermarks and collusion secure fingerprints for digital images

Mel-cepstrum-based steganalysis for VoIP steganography

Steganography and steganalysis in voice-over IP scenarios: operational aspects and first experiences with a new steganalysis tool set