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Trust in cross-media applications is essential to successful collaboration. Cross media service delivery encompasses different types of security incidents and assumes a level of trust on the part of the participants of any one transaction. As enterprises and participants of cross media transactions become more susceptible to security risks facilitated by the heterogeneity of data being exchanged, it is important to develop protective infrastructures. Such infrastructures should enable reporting of security violations or misconduct on a regular basis with effortless incident submission, automatic classification of reported incidents, searching and collective knowledge extraction from similar incidents and sharing of information by authorized users. We report on such a system currently being developed. The Security Incident Sharing and Classification system (SISC), collects incidents in a database, though its incident submission interface, and classifies them according to different parameters. We demonstrate an automatic classification scheme based on the level of incident severity, where severe incidents are processed faster. The system builds trust through its monitoring and recommendation capabilities, thus preparing enterprises to encounter new security incidents that may arise. This is an open, customizable, self-standing risk monitoring system which can be built into any enterprise. The recommendation component of SISC extracts solution scenarios from the gathered knowledge of classified incidents and makes them available to SISC users.

List of Figures. List of Tables. Preface. Acknowledgments. 1. Introduction. 2. Media, Multimedia, and Synchronization Models. 3. Multiple Media Correlation. 4. Algorithms for Multiple Media Correlation. 5. Parallel Text Alignment. 6. Text-To-Speech Alignment. 7. The Xtrieve System. 8. Applications and Future Work. Appendices. Index.

Computed multimedia synchronization and multiple media correlation are new areas of research in multimedia data analysis. As such, the applications and solutions presented in this book are the Genesis of this new research area. This chapter describes many potential applications for multiple media technologies, as well as possibilities for core research in multiple media analysis and computed synchronization. This chapter is representative of planned future work in this field. Some of these applications are already in preliminary development at the DEVLAB and the Michigan State University Media and Entertainment Technologies Laboratory (METLAB), while others represent future research areas proposed or planned.

Chapter 3 presented a general model for multiple media correlation. This chapter presents a specific algorithmic solution strategy for that model. As presented, multiple media correlation is a very general model and a single solution approach encompassing all possible applications is not practical. However, the solution approach presented in this chapter is appropriate for large classes of problems, namely those which can be expressed using media representation graphs (MRGs). Media representation graphs are discussed in Section 5..

This book develops a new framework for computed synchronization and demonstrates it within the context of several applications. A major contribu­tion of this research is the development of a cross-modal information retrieval (CMIR) system that can serve as a test-bed for application of computed synchro­nization technologies: the Xtrieve cross-modal information retrieval system. Xtrieve provides infrastructure in support of media alignment technologies and is the implementation environment for the solutions presented in Chap­ters 5 and 6. Xtrieve also provides a tool for exploring the use of computed synchronization technologies in information retrieval applications.

This chapter develops general models that form the framework for computed synchronization solutions. The goal of computed synchronization is the automatic determination of causal and spatial synchronization among media objects. The models that are developed provide a basis for the construction of solutions to real-world problems in media synchronization, as well as a basis for proving solution validity. Techniques based on these models are collectively referred to as multiple media correlation (MMC). Chapter 4 presents algorithmic approaches to solving these models.

Text-to-speech alignment is the alignment of a textual transcript to an audio stream. The computed synchronization data is a mapping from words in the text transcript to temporal intervals in the audio. This alignment provides a basic tool that facilitates many applications and has wide-spread general applicability.

The advent of modern electronic multimedia publishing and delivery systems extends previous modes of publishing to incorporate new media and new features. For example, a growing number of conferences, particularly in the field of Computer Science, are creating electronic proceedings that are made available on CD-ROM or via networks and are extending the proceedings to incorporate non-textual materials, such as video or audio segments, and new features, such as retrieval mechanisms and hypertext cross-linking. In this paper we discuss interactive multimedia publications (IMMpubs), drawing on our experience creating such electronic conference proceedings and other multimedia publications. Our discussions emphasize the continuing role of text, highlight the pitfalls of some publication systems, and illustrate the potentials of interactive multimedia publications.