Advances in Artificial Intelligence for Privacy Protection and Security.
Title:
Advances in Artificial Intelligence for Privacy Protection and Security.
Author:
Solanas, Agusti.
ISBN:
9789812790330
Personal Author:
Physical Description:
1 online resource (402 pages)
Series:
Intelligent Information Systems ; v.1
Intelligent Information Systems
Contents:
Contents -- Preface -- 1. Introduction A. Solanas and A. Mart¶³nez-Ballest¶e -- 1.1. Organization of the book -- References -- PART 1: A Brief Introduction to Privacy and Security -- 2. An Introduction to Privacy Aspects of Information and Communication Technologies A. Martinez-Balleste and A. Solanas -- Contents -- 2.1. Introduction -- 2.2. Privacy and the Internet -- 2.2.1. Monitoring User Activity -- 2.2.1.1. Tracking Cookies -- 2.2.1.2. Spyware -- 2.2.1.3. Social Engineering Attacks -- 2.2.2. Privacy in Modern Web Services -- 2.2.2.1. Privacy in Social Networks -- 2.2.2.2. Privacy in E-Commerce -- 2.2.3. The Big Brothers of Internet -- 2.3. Privacy in Databases -- 2.3.1. Privacy of the Respondents -- 2.3.2. User Privacy -- 2.4. Privacy in Ubiquitous Computing -- 2.4.1. Location-Based Services -- 2.4.1.1. TTP-Based Schemes -- 2.4.1.2. TTP-Free Proposals -- 2.4.2. Radio-Frequency Identic̄ation -- 2.5. Conclusions -- Disclaimer and Acknowledgements -- References -- 3. An Overview of Information Security A. Ribagorda Garnacho, A. I. Gonz¶alez-Tablas Ferreres, A. Alcaide Raya -- Contents -- 3.1. Introduction -- 3.2. Vulnerabilities -- 3.3. Threats -- 3.4. Countermeasures -- 3.5. Authentication mechanisms -- 3.5.1. Something you know -- 3.5.2. Something you are -- 3.5.3. Something you have -- 3.6. Access control mechanisms -- 3.6.1. Access control policies -- 3.6.2. Access control models -- 3.6.2.1. Access matrix model -- 3.6.2.2. Mandatory access control models -- 3.7. Data encipherment mechanisms -- 3.7.1. Attacks -- 3.7.2. Cryptosystems classification -- 3.7.2.1. Substitution, transposition and product ciphers -- 3.7.2.2. Symmetric or secret key cryptosystems -- 3.7.2.3. Asymmetric or public key cryptosystems -- 3.7.3. Stream and block cryptosystems -- 3.8. Digital signature mechanism -- 3.9. Digital certificates -- 3.10. Audit logs.
3.11. Physical security -- 3.11.1. Intrusion prevention -- 3.11.2. Electromagnetic emanations -- 3.11.3. Physical access control systems -- References -- PART 2: Privacy Protection by means of Artic̄ial Intelligence -- 4. Data Mining in Large Databases
5.6.4. ONN evaluation -- 5.7. Conclusions -- Acknowledgments -- References -- 6. Multi-Objective Evolutionary Optimization in Statistical Disclosure Control R. Dewri, I. Ray, I. Ray and D. Whitley -- Contents -- 6.1. Introduction -- 6.2. Multi-objective Optimization -- 6.3. Statistical Disclosure Control -- 6.3.1. Preserving privacy -- 6.3.2. Estimating information loss -- 6.4. Evolutionary Optimization -- 6.4.1. Multi-objective analysis -- 6.4.1.1. In the absence of suppression -- 6.4.1.2. With pre-specified suppression tolerance -- 6.4.1.3. For comprehensive overview -- 6.4.2. Solution encoding -- 6.4.3. Non-dominated Sorting Genetic Algorithm-II -- 6.4.4. Crossover for constrained attributes -- 6.4.5. Population initialization -- 6.5. Some Empirical Results -- 6.6. Summary -- Acknowledgment -- References -- 7. On the Definition of Cluster-Specic̄ Information Loss Measures V. Torra -- Contents -- 7.1. Introduction -- 7.2. Preliminaries -- 7.2.1. Protection methods -- 7.2.2. Generic information loss measures -- 7.2.3. Fuzzy sets, fuzzy partitions, and fuzzy clustering -- 7.3. Information loss measures for clustering -- 7.3.1. Comparison of crisp clusters -- 7.3.2. Comparison of fuzzy clusters -- 7.3.3. Extensions using intuitionistic fuzzy sets -- 7.4. Conclusions and future work -- Acknowledgments -- References -- 8. Privacy Preserving and Use of Medical Information in a Multiagent System K. Gibert, A. Valls, L. Lhotska and P. Aubrecht -- Contents -- 8.1. Introduction -- 8.2. Privacy preserving and security in a distributed platform for medical domains -- 8.3. Identification and authentication -- 8.4. Authorization and information access rights -- 8.4.1. Ontologies -- 8.4.2. Actor Profile Ontologies -- 8.5. Multiagent system -- 8.6. Intermediate layer for knowledge-interface communications -- 8.7. Private data protection.
8.8. A real case: the K4Care project -- 8.8.1. The K4Care model -- 8.8.2. The knowledge management -- 8.8.3. The K4Care system architecture -- 8.9. Discussion -- References -- PART 3: Security by means of Artificial Intelligence -- 9. Perimeter Security on Noise-Robust Vehicle Detection Using Nonlinear Hebbian Learning B. Lu, A. Dibazar, S. George and T. W. Berger -- Contents -- 9.1. Introduction -- 9.2. Description of the Proposed System -- 9.3. Unsupervised Nonlinear Hebbian Learning -- 9.3.1. Linear Hebbian Learning -- 9.3.2. Nonlinear Hebbian Learning -- 9.3.3. Nonlinear Activation Function -- 9.4. Real-time Field Testing Results -- 9.5. Simulation Results -- 9.5.1. Decision I: Vehicle vs. Non-vehicle Recognition -- 9.5.2. Decision II: Vehicle Type Identic̄ation -- 9.6. Conclusion and Discussion -- Acknowledgment -- References -- 10. Texture-Based Approach for Computer Vision Systems in Autonomous Vehicles D. Puig, J. Melendez and M. A. Garcia -- Contents -- 10.1. Introduction -- 10.2. Background -- 10.3. Per-Pixel Texture Classifier -- 10.3.1. Feature Extraction -- 10.3.2. Texture Model Reduction -- 10.3.3. K-Nearest Neighbors Classification -- 10.3.4. Post-Processing -- 10.4. Automatic Parameter Selection -- 10.5. Experimental Results -- 10.6. Conclusions and Future Work -- Acknowledgements -- References -- 11. An Aggression Detection System for the Train Compartment Z. Yang, S. Fitrianie, D. Datcu and L. Rothkrantz -- Contents -- 11.1. Introduction -- 11.2. Related work -- 11.2.1. Automated aggression detection -- 11.2.2. Human based event reporting -- 11.3. System overview -- 11.4. Knowledge representation -- 11.4.1. Motivation -- 11.4.2. Ontology overview -- 11.4.3. The static context -- 11.4.4. Dynamic context -- 11.5. Automated aggression detection -- 11.5.1. Approach -- 11.5.2. Fusion and classification.
11.5.2.1. Facial expression recognition -- 11.5.2.2. Emotion recognition from speech -- 11.5.2.3. Results for the extraction of emotion-related features -- 11.5.2.4. Event and activity recognition -- 11.5.3. Reasoning model -- 11.5.4. Implementation -- 11.6. Icon-based reporting tool on smart phones -- 11.6.1. The icon interface -- 11.6.2. System knowledge representation -- 11.7. Communication framework -- 11.8. The operator room -- 11.8.1. Icon language message interpreter -- 11.8.1.1. Multiple messages processor -- 11.9. Evaluation -- 11.10. Conclusions and future work -- References -- 12. K-Means Clustering for Content-Based Document Management in Intelligence S. Decherchi, P. Gastaldo and R. Zunino -- Contents -- 12.1. Introduction -- 12.2. Document Clustering in Text Mining for Security Applications -- 12.2.1. Document indexing -- 12.2.2. Document clustering -- 12.3. Hybrid Approach to k-Means Clustering -- 12.3.1. Document distance measure -- 12.3.1.1. Algorithm for generating v00(D) -- 12.3.2. Kernel k-means -- 12.3.2.1. The feature-space version of k-means clustering -- 12.4. The Document-Clustering Framework -- 12.4.1. The document-clustering algorithm -- 12.4.1.1. The document-clustering procedure -- 12.4.2. Dimension reduction for document clustering by using random projections -- 12.4.3. Computational complexity -- 12.5. Experimental Results -- 12.5.1. Reuters-21578 -- 12.5.2. Enron dataset -- 12.6. Conclusions -- References -- 13. Genetic Algorithms for Designing Network Security Protocols L. Zarza, J. Forn¶e, J. Pegueroles and M. Soriano -- Contents -- 13.1. Introduction -- 13.2. Genetic algorithms -- 13.2.1. Definitions and terminology -- 13.2.2. General characteristics of genetic algorithms -- 13.2.3. Search space -- 13.2.4. Operation of a simple genetic algorithm -- 13.2.4.1. Selection phase -- 13.2.4.2. Modification phase.
13.2.4.3. Evaluation phase.
Abstract:
In this book, we aim to collect the most recent advances in artificial intelligence techniques (i.e. neural networks, fuzzy systems, multi-agent systems, genetic algorithms, image analysis, clustering, etc), which are applied to the protection of privacy and security. The symbiosis between these fields leads to a pool of invigorating ideas, which are explored in this book. On the one hand, individual privacy protection is a hot topic and must be addressed in order to guarantee the proper evolution of a modern society. On the other, security can invade individual privacy, especially after the appearance of new forms of terrorism. In this book, we analyze these problems from a new point of view. Sample Chapter(s). Chapter 1: Introduction (281 KB). Contents: A Brief Introduction to Privacy and Security: An Introduction to Privacy Aspects of Information and Communication Technologies (A Martínez-Ballesté & A Solanas); An Overview of Information Security (A Ribagorda Garnacho et al.); Privacy Protection by Means of Artificial Intelligence: Data Mining in Large Databases - Strategies for Managing the Trade-Off Between Societal Benefit and Individual Privacy (M Schmid); Desemantization for Numerical Microdata Anonymization (J Pont-Tuset et al.); Multi-Objective Evolutionary Optimization in Statistical Disclosure Control (R Dewri et al.); On the Definition of Cluster-Specific Information Loss Measures (V Torra); Privacy Preserving and Use of Medical Information in a Multiagent System (K Gibert et al.); Security by Means of Artificial Intelligence: Perimeter Security on Noise-Robust Vehicle Detection Using Nonlinear Hebbian Learning (B Lu et al.); Texture-Based Approach for Computer Vision Systems in Autonomous Vehicles (D Puig et al.); An Aggression Detection System for the Train Compartment (Z Yang et al.); K-Means Clustering for Content-Based Document
Management in Intelligence (S Decherchi et al.); Genetic Algorithms for Designing Network Security Protocols (L Zarza et al.); Evolving Strategy-Based Cooperation in Wireless Mobile Ad Hoc Networks (M Seredynski et al.). Readership: Researchers, academics and graduate students in artificial intelligence, security and privacy.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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