Secure Information Management Using Linguistic Threshold Approach

In recent years, cryptographic techniques for protecting and hiding secret information have been included in directions of research on intelligent information management. Data can be managed securely due to the use of algorithms for ensuring the confidentiality of data, information splitting techniques as well as protocols for sharing information and methods of its reconstruction.
This is why techniques of advanced splitting and reconstruction of information form the primary subject of Secure Information Management Using Linguistic Threshold Approach, whose main purpose is to discuss the so-called linguistic threshold schemes for information sharing. An attempt is also made to describe the opportunities of using these techniques to create new models of managing strategic information shared within a commercial organisation or a state institution. Such information is specially protected, and its contents are used only if the authorised users are enabled to access it. This monograph attempts to define a model structure of information flow and for assigning information shares to particular groups of individuals concerned. The proposed information flow model can be integrated into practical solutions within any organisation or institution, improving the functionality of its legacy information systems.
The use of strong mathematical cryptographic models to manage information constitutes a scientific innovation and a demonstration of the methods and opportunities of using advanced techniques for confidentially exchanging information in tasks supporting data flow within a commercial organisation.
The interdisciplinary nature of the solutions proposed means that the subject of linguistic threshold schemes forming part of intelligent information management becomes a new challenge for the research and application work carried out.
The authors of this monograph hope that it will guide readers on an interesting journey through the cutting edge solution in the field of secure information management.

List of contents

Preface.- Introduction.- Fields of Application, Methods of and Current Trends in Information Management.- Types of Information Splitting and Sharing Techniques.- Model of Multilevel Information Splitting and Management in an Organization.- Proposition of Sharing Techniques Based on the Mathematical Linguistic Approach.- Methodological Aspects of Information Sharing and Management in Organizations.- Features of Linguistic Threshold Schemes.- Index.

Summary

In recent years, cryptographic techniques for protecting and hiding secret information have been included in directions of research on intelligent information management. Data can be managed securely due to the use of algorithms for ensuring the confidentiality of data, information splitting techniques as well as protocols for sharing information and methods of its reconstruction.
This is why techniques of advanced splitting and reconstruction of information form the primary subject of Secure Information Management Using Linguistic Threshold Approach, whose main purpose is to discuss the so-called linguistic threshold schemes for information sharing. An attempt is also made to describe the opportunities of using these techniques to create new models of managing strategic information shared within a commercial organisation or a state institution. Such information is specially protected, and its contents are used only if the authorised users are enabled to access it. This monograph attempts to define a model structure of information flow and for assigning information shares to particular groups of individuals concerned. The proposed information flow model can be integrated into practical solutions within any organisation or institution, improving the functionality of its legacy information systems.
The use of strong mathematical cryptographic models to manage information constitutes a scientific innovation and a demonstration of the methods and opportunities of using advanced techniques for confidentially exchanging information in tasks supporting data flow within a commercial organisation.
The interdisciplinary nature of the solutions proposed means that the subject of linguistic threshold schemes forming part of intelligent information management becomes a new challenge for the research and application work carried out.The authors of this monograph hope that it will guide readers on an interesting journey through the cutting edge solution in the field of secure information management.

Additional text

From the reviews:
“The book brings the reader to the forefront of mathematical foundations of information sharing and splitting. … The most distinguished contribution of the authors is the mathematical linguistic approach to information sharing, and it makes the book worthwhile reading for researchers. However, the book is highly recommended for not only the researchers who work on information management, but also the institutions and commercial business having a hierarchical organisation, because of providing highly practical security for them.” (Korhan Günel, zbMATH, Vol. 1283, 2014)

Report

From the reviews:
"The book brings the reader to the forefront of mathematical foundations of information sharing and splitting. ... The most distinguished contribution of the authors is the mathematical linguistic approach to information sharing, and it makes the book worthwhile reading for researchers. However, the book is highly recommended for not only the researchers who work on information management, but also the institutions and commercial business having a hierarchical organisation, because of providing highly practical security for them." (Korhan Günel, zbMATH, Vol. 1283, 2014)

Product details

• Authors: Marek Ogiela, Marek R Ogiela, Marek R. Ogiela, Urszula Ogiela
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Released: 30.11.2013
• EAN: 9781447150152
• ISBN: 978-1-4471-5015-2
• No. of pages: 136
• Dimensions: 162 mm x 15 mm x 242 mm
• Weight: 370 g
• Illustrations: XIII, 136 p.
• Series: Advanced Information and Knowledge Processing; Advanced Information and Knowledge Processing
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT