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Intelligent Data Analytics for Terror Threat Prediction. Группа авторов
Читать онлайн.Название Intelligent Data Analytics for Terror Threat Prediction
Год выпуска 0
isbn 9781119711513
Автор произведения Группа авторов
Жанр Программы
Издательство John Wiley & Sons Limited
7 Chapter 12Table 12.1 Benefits & Snag of security schemes in WSN.
8 Chapter 14Table 14.1 Functionality of USB charging cable.
List of Illustrations
1 Chapter 1Figure 1.1 Social networks [23].Figure 1.2 Classification of rumor and non-rumor.Figure 1.3 Rumor classification process.Figure 1.4 Naïve Bayes classifier.Figure 1.5 Hyperplane in 2-D and 3-D.Figure 1.6 Combating misinformation in Instagram [33].Figure 1.7 Network topology.Figure 1.8 SI model.Figure 1.9 SIS model.Figure 1.10 SIR model.Figure 1.11 SIRS model.Figure 1.12 Centrality measures.Figure 1.13 Rumor source detection process.
2 Chapter 2Figure 2.1 Advancement of Internet through ARPANET to IoT and M2M.Figure 2.2 Machine knowledge points of view for IoT through M2M with Cyber Secur...Figure 2.3 IoT Theoretical Top 10 Risks.Figure 2.4 Top 5 Functional Risks and Vulnerabilities.Figure 2.5 GSM-based modules with wireless connectivity.
3 Chapter 4Figure 4.1 Frame work of military GIS.Figure 4.2 Various applications of GIS in defense strategy.Figure 4.3 Cartographic model for land management in hilly area.Figure 4.4 Digital Elevation Model.Figure 4.5 Triangulated Irregular Network (TIN) Model.Figure 4.6 Hillshade analysis model for terrain analysis.
4 Chapter 5Figure 5.1 Broad steps followed in text mining.Figure 5.2 Process of text mining.Figure 5.3 Work flow of text mining.Figure 5.4 Detailed workflow of proposed approach.Figure 5.5 Process followed to obtain similarity score.Figure 5.6 Similarity and accuracy for the keyword ‘Authentication’.Figure 5.7 Ranking graph of document and similarity for keyword ‘SQL Injection’.Figure 5.8 Accuracy for searching vulnerable keywords.
5 Chapter 6Figure 6.1 Overall architecture of the proposed method.
6 Chapter 7Figure 7.1 General flow of biometric systems.Figure 7.2 Biometric traits.Figure 7.3 Biometric framework.Figure 7.4 Biometric applications.Figure 7.5 Soft biometric classification.Figure 7.6 Soft Biometric System Interface.Figure 7.7 Surveillance system.Figure 7.8 Accuracy recognition.Figure 7.9 Proposed Work Flow Diagram.Figure 7.10 Proposed Frame Work.Figure 7.11 Intelligent Identification System.
7 Chapter 8Figure 8.1 Botnet life cycle.Figure 8.2 Different botnet detection methods.Figure 8.3 Block diagram of proposed methodology.Figure 8.4 Decision tree obtained using proposed approach.Figure 8.5 Percentage accuracy of various machine learning model and proposed mo...
8 Chapter 9Figure 9.1 Face.Figure 9.2 Hand geometry.Figure 9.3 Fingerprint.Figure 9.4 Voice detection.Figure 9.5 Iris.Figure 9.6 Keystrokes.Figure 9.7 (a), (b) Forms of linking biometric framework with cryptanalysis.
9 Chapter 10Figure 10.1 Architecture of Hadoop.Figure 10.2 Types of Homomorphic Encryption.
10 Chapter 12Figure 12.1 Architecture of WSN.Figure 12.2 Different parameters for security of information collection.Figure 12.3 Various standards for attack detection.
11 Chapter 14Figure 14.1 Cybercrime evolution.Figure 14.2 MITM attack.Figure 14.3 Steps of Phishing attack.Figure 14.4 A sample email.Figure 14.5 Session hijacking levels.Figure 14.6 A sample session hijacking.Figure 14.7 Steps of XSS attack.Figure 14.8 SQL injection interpretation.Figure 14.9 A sample DOS attack.Figure 14.10 Differentiation between dark, deep & surface web.Figure 14.11 Tor browser functionality.
Guide
1 Cover
5 Preface
7 Index
Pages
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2 ii
3 iii
4 iv
5 xv
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8 xviii
9 xix
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