The Editors |
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xv | |
Contributors |
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xvii | |
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1 Information Security Policy and Standards |
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1 | (12) |
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1 | (1) |
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1 | (2) |
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1.3 Structure of Policy Documents |
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3 | (2) |
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1.4 Governance (Understanding the Ownership, Responsibilities, and Accountabilities) |
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5 | (1) |
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1.5 Writing Effective Policies (Characteristics and Attributes of an Effective Policy Document) |
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5 | (3) |
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1.6 Policy Life Cycle (Policy from Cradle to Grave) |
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8 | (4) |
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8 | (1) |
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8 | (1) |
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8 | (1) |
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1.6.1.3 Stakeholder Review |
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9 | (1) |
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1.6.1.4 Identify Key Success Factors and Key Performance Indicators |
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9 | (1) |
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9 | (1) |
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9 | (1) |
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1.6.2.1 Communication and Awareness |
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9 | (1) |
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1.6.2.2 Create/Update Processes |
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10 | (1) |
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1.6.2.3 Provide Tools Where Possible |
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10 | (1) |
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10 | (1) |
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1.6.3.1 Monitoring Compliance |
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10 | (1) |
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1.6.3.2 Influencing User's Behavior (The Carrot-and-Stick Approach) |
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11 | (1) |
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1.6.4 Assess, Review, and Update |
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11 | (1) |
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12 | (1) |
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12 | (1) |
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2 Vulnerability Management |
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13 | (12) |
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13 | (1) |
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13 | (1) |
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14 | (1) |
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15 | (1) |
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2.5 Why Is Software Vulnerable? |
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15 | (1) |
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2.6 Vulnerability Management |
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15 | (4) |
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2.6.1 Discovering Vulnerabilities |
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16 | (1) |
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2.6.1.1 Identifying the Types of Attacks |
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16 | (1) |
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2.6.1.2 Inventory of Assets |
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17 | (1) |
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2.6.2 Assessing Vulnerabilities |
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17 | (2) |
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19 | (1) |
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2.6.4 Remediating and Verifying |
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19 | (1) |
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2.7 Participants in Vulnerability Management |
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19 | (1) |
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2.8 Vulnerability Analysis Tools |
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20 | (1) |
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2.9 Best Practices for Vulnerability Management |
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21 | (1) |
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2.10 A Case Study in Vulnerability Management: Equifax |
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21 | (2) |
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2.10.1 Identifying/Discovering the Vulnerability |
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22 | (1) |
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2.10.2 Assessment of the Vulnerability |
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22 | (1) |
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2.10.3 Reporting the Vulnerability |
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23 | (1) |
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2.10.4 Remediating and Verifying |
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23 | (1) |
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23 | (2) |
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3 Identity Theft and Prevention |
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25 | (18) |
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25 | (1) |
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26 | (3) |
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3.3 Research Model and Hypothesis |
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29 | (3) |
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32 | (2) |
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32 | (1) |
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32 | (1) |
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3.4.3 Instrument Development |
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33 | (1) |
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34 | (3) |
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34 | (1) |
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3.5.2 Exploratory Factor Analysis |
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35 | (1) |
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3.5.3 Confirmatory Factor Analysis |
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35 | (1) |
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3.5.4 Structural Model and Hypotheses Testing |
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36 | (1) |
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37 | (2) |
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39 | (1) |
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39 | (4) |
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4 Organization Security Policies and Their After Effects |
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43 | (18) |
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43 | (5) |
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4.1.1 What Does Security Policy Mean? |
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43 | (1) |
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4.1.2 Why Do You Need a Security Policy? |
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44 | (1) |
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4.1.3 How to Develop Policy |
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44 | (2) |
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4.1.4 How Can Policy Operation Be Made Truthful? |
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46 | (1) |
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47 | (1) |
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4.1.6 Security Policy of Outsiders |
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47 | (1) |
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48 | (4) |
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4.2.1 Types of Information Security Policies |
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48 | (1) |
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4.2.2 Development of Information Security Policy |
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49 | (1) |
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4.2.3 Approaches to the Implementation of Information Security Policy |
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50 | (1) |
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4.2.4 Policies, Standards and Practices |
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50 | (1) |
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4.2.5 Governance of Information Security |
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51 | (1) |
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4.3 Success Factors of Security Policies in Organizations |
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52 | (2) |
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4.3.1 Awareness and Training |
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52 | (1) |
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53 | (1) |
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53 | (1) |
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4.3.4 Information Security Policy Enforcement |
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54 | (1) |
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4.3.5 Organizational Mission |
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54 | (1) |
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4.4 Case Studies of Security Policies in Organizations |
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54 | (1) |
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54 | (1) |
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55 | (2) |
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4.4.1 Organizational Objectives and Goals as Derived from the Case Studies |
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57 | (1) |
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57 | (1) |
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57 | (4) |
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5 Cyber-Attacks and Their Impact on Real Life: What Are Real-Life Cyber-Attacks, How Do They Affect Real Life and What Should We Do About Them? |
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61 | (18) |
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61 | (2) |
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5.1.1 Definition of Cyber-Attacks |
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61 | (1) |
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5.1.2 Cyber-Attacks in Recent Days |
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62 | (1) |
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5.1.3 Why Is it Essential to Prevent Cyber-Attacks? |
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62 | (1) |
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5.1.4 Types of Cybersecurity Attacks |
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62 | (1) |
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63 | (5) |
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63 | (2) |
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5.2.2 The Cyber-Battlefield |
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65 | (1) |
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5.2.3 Effective Limitations of Cyber-Warfare |
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66 | (1) |
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67 | (1) |
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67 | (1) |
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67 | (1) |
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67 | (1) |
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67 | (1) |
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5.3 Development of Cyber-Warfare and Cyber-Conflict |
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68 | (1) |
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5.4 Emerging Cyber-Attacks |
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69 | (1) |
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5.5 Cybersecurity Attacks |
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69 | (1) |
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5.6 Cyber Defense Best Practices and Protection |
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70 | (1) |
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5.6.1 Cyber Defense for Industries |
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70 | (1) |
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5.6.2 Cyber Defense for Individuals |
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70 | (1) |
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5.6.3 Nation-State Cyber-Attacks |
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71 | (1) |
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5.6.4 Examples of Cyber-Warfare |
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71 | (1) |
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Case Study 1 Olympic Games |
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71 | (1) |
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Case Study 2 Ukrainian Power Grid |
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72 | (1) |
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Case Study 3 Russian Hackers Tracking Ukrainian Artillery |
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72 | (1) |
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Case Study 4 Sony Corp's Hollywood Studio |
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72 | (1) |
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Case Study 5 Estonian Government Attack |
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73 | (1) |
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5.7 Impact of the Attacks |
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73 | (2) |
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5.7.1 Breakdown of Cyber-Tools Used |
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73 | (1) |
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73 | (1) |
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74 | (1) |
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74 | (1) |
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5.7.5 Confidential Data Acquisition |
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74 | (1) |
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5.7.6 Distributed Denial-of-Service (DDoS) |
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74 | (1) |
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5.7.7 Equipment Distribution |
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75 | (1) |
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5.7.8 Critical Infrastructure Attacks |
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75 | (1) |
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5.7.9 Compromised Fake Hardware |
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75 | (1) |
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5.7.10 Theft or Hardware Destruction |
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75 | (1) |
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75 | (1) |
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76 | (3) |
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6 Cryptography and Steganography Techniques |
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79 | (14) |
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79 | (1) |
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79 | (2) |
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6.2.1 The Oldest Cryptographic Technique--Hieroglyphs |
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80 | (1) |
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81 | (3) |
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6.3.1 Different Techniques of Steganography |
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82 | (1) |
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6.3.1.1 Text Steganography |
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82 | (1) |
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6.3.1.2 Auditory Steganography |
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82 | (1) |
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6.3.1.3 Cinematic Steganography |
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82 | (1) |
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6.3.1.4 Visual Steganography |
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83 | (1) |
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6.3.2 Applications of Steganography |
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84 | (1) |
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6.4 Cryptography Concepts |
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84 | (4) |
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6.4.1 Types of Cryptography |
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86 | (1) |
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6.4.1.1 Symmetric Cryptography |
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86 | (2) |
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6.5 Benefits of a Hybrid Approach: Steganography and Cryptography |
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88 | (1) |
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89 | (1) |
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90 | (1) |
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90 | (3) |
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7 An FPGA-Based Advanced Lightweight Cryptography Architecture for IoT Security and Its Cryptanalysis |
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93 | (14) |
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7.1 Introduction: Background and Driving Forces |
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93 | (3) |
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94 | (2) |
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7.2 The Lightweight Security Architecture |
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96 | (4) |
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7.2.1 External Signals and Buses |
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96 | (1) |
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97 | (1) |
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7.2.3 Internal Memory Registers |
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97 | (1) |
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7.2.4 Internal Encryption and Decryption Module |
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97 | (1) |
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7.2.5 Internal Mux-DeMux Module |
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98 | (1) |
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7.2.6 Internal Control Unit |
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99 | (1) |
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100 | (1) |
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101 | (1) |
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7.5 Simulation-Based Results |
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102 | (1) |
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103 | (1) |
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103 | (1) |
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104 | (3) |
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8 An Overview of Digital Image Forensics: Image Morphing and Forgery Detection Algorithms |
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107 | (14) |
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107 | (2) |
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8.1.1 A Sequential Processing Cycle of a Digital Image |
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108 | (1) |
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109 | (4) |
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8.2.1 Processes in Image Morphing |
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110 | (1) |
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8.2.2 Image Morphing Algorithms |
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110 | (1) |
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110 | (1) |
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111 | (1) |
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8.2.2.3 Radial Basis Function (RBF) Morphing |
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112 | (1) |
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8.2.2.4 Energy Minimization Morphing |
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112 | (1) |
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8.2.3 Multilevel Free Form Deformation (MFFD) |
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112 | (1) |
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8.3 Traces in Image Forensics |
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113 | (1) |
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8.3.1 Acquisition Phase Traces |
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113 | (1) |
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8.3.2 Coding Phase Traces |
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114 | (1) |
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8.3.3 Editing Phase Traces |
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114 | (1) |
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8.4 Classification of Forgery Detection (Authentication) Techniques |
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114 | (2) |
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8.5 Copy-Move Forgery Detection Techniques |
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116 | (1) |
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117 | (1) |
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118 | (1) |
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118 | (3) |
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9 Analysis of Classification-Based Intrusion-Detection Techniques |
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121 | (22) |
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121 | (1) |
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9.2 Intrusion Detection Systems (IDSs) |
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122 | (7) |
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9.2.1 Requirements of IDSs |
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123 | (1) |
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9.2.2 Categorization of the IDS |
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123 | (1) |
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123 | (1) |
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9.2.2.2 Types of Intrusion |
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124 | (1) |
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9.2.2.3 Methodologies for Detecting Attacks |
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124 | (2) |
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9.2.2.4 Audit Statistics Source |
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126 | (1) |
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9.2.2.5 Accumulated Statistics Computing Region |
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127 | (1) |
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127 | (1) |
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128 | (1) |
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9.2.3 Decision-Making Inside the IDS |
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128 | (1) |
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128 | (1) |
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9.2.5 Further Literature About WSN |
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129 | (1) |
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9.3 Application of IDS in MANET and WSN |
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129 | (6) |
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9.3.1 Primarily Agent Based Dispensed and Collaborative IDSs |
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129 | (2) |
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9.3.2 Clustering (Hierarchical) Based IDSs |
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131 | (1) |
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9.3.3 Statistical Detection Based IDSs |
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132 | (1) |
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9.3.4 Misuse Detection-Based IDS |
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132 | (1) |
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9.3.5 Reputation (Trust)-Based IDSs |
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132 | (1) |
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133 | (1) |
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9.3.7 Primarily Sector Based IDS |
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133 | (1) |
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9.3.8 Game Idea Based IDSs |
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134 | (1) |
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9.3.9 Genetic Algorithm Based IDS |
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134 | (1) |
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135 | (1) |
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9.4 Intrusion Detection System in WSN 212 |
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135 | (5) |
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9.4.1 Restrictions and Research Challenges in WSN |
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136 | (1) |
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9.4.2 Differences Between MANETs and WSNs |
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136 | (1) |
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137 | (1) |
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9.4.3.1 Grouping Based IDSs |
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137 | (1) |
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9.4.3.2 Centralized and Collaborative IDSs |
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138 | (1) |
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9.4.3.3 Statistical Detection Based IDSs |
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138 | (1) |
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9.4.3.4 IDSs Based on Game Theory |
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139 | (1) |
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9.4.3.5 Anomaly Based Detection of IDSs |
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139 | (1) |
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9.4.3.6 Totally IDS Based Watchdog |
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139 | (1) |
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9.4.3.7 Reputation (Trust) Based IDS |
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139 | (1) |
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9.5 Future Directions in the Selection of IDS for WSN |
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140 | (1) |
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140 | (1) |
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140 | (3) |
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10 Cryptocurrency and Blockchain |
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143 | (16) |
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10.1 Introduction--Definition of Blockchain: A Multiple Faced Technology |
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143 | (1) |
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10.2 The Basic Working of Blockchain |
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144 | (1) |
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10.2.1 A Distributed Database: Blockchain |
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144 | (1) |
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10.2.2 Bye-Bye Middleman? |
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144 | (1) |
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10.3 The Blockchain Agreement Mechanisms |
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144 | (1) |
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10.3.1 Cryptographic Offers Proof of Work |
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145 | (1) |
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145 | (1) |
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10.3.3 Additional Mechanisms |
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145 | (1) |
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10.4 What Are Cryptocurrencies? |
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145 | (3) |
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10.4.1 International Monetary Fund (IMF) |
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146 | (1) |
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10.4.2 Bank for International Settlements |
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146 | (1) |
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10.4.3 European Banking Authority (EBA) |
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146 | (1) |
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10.4.4 European Securities and Markets Authority (ESMA) |
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147 | (1) |
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147 | (1) |
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10.4.6 Financial Action Task Force |
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147 | (1) |
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147 | (1) |
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10.5 Advanced Types of Money--Tokens--Cryptosecurities |
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148 | (1) |
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10.5.1 Computerized Monetary Requirements--Tokens |
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148 | (1) |
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10.5.2 Advanced Kinds of Money--Cryptosecurities |
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148 | (1) |
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10.6 Computerized Kinds of Cash--Blockchain |
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148 | (2) |
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10.6.1 Who Are the Players Being Referred To? |
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148 | (1) |
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10.6.2 Cryptographic Cash Customers |
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149 | (1) |
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149 | (1) |
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10.6.4 Computerized Money Exchanges |
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149 | (1) |
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150 | (1) |
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150 | (1) |
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10.7 Orchestrating CRYPTOCURRENCIES--Checking the Crypto-Market |
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150 | (1) |
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10.8 Bitcoin and Beyond: Virtual Styles of Money with the Highest Market Capitalization |
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151 | (1) |
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10.8.1 Wave (XRP) Is Legitimately Adaptable into Fiat Coins |
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152 | (1) |
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10.8.2 Wave (XRP) Is a Vehicle of Trade |
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152 | (1) |
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152 | (1) |
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152 | (1) |
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152 | (1) |
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10.9.2 Stellar Runs on a Permissionless Blockchain |
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152 | (1) |
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10.9.3 Lumens Are Pseudo-Processed Coins |
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153 | (1) |
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153 | (1) |
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10.10.1 Cardano's Operations |
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153 | (1) |
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153 | (1) |
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153 | (1) |
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10.11.2 NEO's GAS Offers Digital Coins |
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153 | (1) |
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154 | (1) |
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10.12.1 Monero's Operations |
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154 | (1) |
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10.12.2 Monero Is a Permissionless Blockchain |
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154 | (1) |
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10.12.3 Monero Is Obviously Convertible into Fiat Cash |
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154 | (1) |
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10.12.4 Monero Is a Digital Trade |
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154 | (1) |
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10.12.5 Monero Is an Exchange Coin |
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154 | (1) |
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10.12.5.1 Ring Secret Transactions |
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154 | (1) |
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10.12.5.2 Stealth Addresses |
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155 | (1) |
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10.12.5.3 The Project--Kovri |
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155 | (1) |
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155 | (1) |
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10.13.1 Dash's Operations |
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155 | (1) |
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10.13.2 Dash Is Unmistakably Convertible into Fiat Cash |
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156 | (1) |
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10.13.3 Dash Is a Vehicle of Trade |
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156 | (1) |
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10.13.4 Dash Is a (Discretionary) Confusing Coin |
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156 | (1) |
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10.14 Conclusion: A Taxonomy and Time Frame of Cryptocurrencies |
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156 | (2) |
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156 | (2) |
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158 | (1) |
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11 Cyber Security in Cloud Platforms |
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159 | (12) |
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11.1 Introduction to Cloud Infrastructure |
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159 | (1) |
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11.2 Cloud Deployment and Services Models |
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159 | (2) |
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160 | (1) |
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160 | (1) |
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160 | (1) |
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11.2.4 Infrastructure as a Service (IaaS) |
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160 | (1) |
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11.2.5 Platform as a Service (PaaS) |
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161 | (1) |
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11.2.6 Software as a Service (SaaS) |
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161 | (1) |
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11.3 Benefits of Cloud Computing |
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161 | (1) |
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162 | (1) |
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11.5 Issues and Challenges |
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163 | (1) |
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11.5.1 Exfiltration of Encrypted Data |
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163 | (1) |
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11.5.2 Lance Phishing Campaign |
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163 | (1) |
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163 | (1) |
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163 | (1) |
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163 | (1) |
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163 | (1) |
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164 | (1) |
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11.6 Cyber Security Mechanism |
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164 | (1) |
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11.7 Solution: Proposed Framework for Security in Cloud Platform |
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165 | (4) |
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166 | (1) |
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166 | (1) |
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11.7.2.1 User Access Control |
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167 | (1) |
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167 | (1) |
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167 | (1) |
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167 | (1) |
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168 | (1) |
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168 | (1) |
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168 | (1) |
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168 | (1) |
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169 | (1) |
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169 | (1) |
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169 | (2) |
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12 Biometrics-Unique Identity Verification System |
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171 | (10) |
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12.1 Introduction to Biometrics |
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171 | (1) |
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12.2 Authentication vs Verification |
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172 | (1) |
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12.3 Types of Biometrics: Physical and Behavioral Biometrics |
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172 | (3) |
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12.3.1 Physical Biometrics |
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174 | (1) |
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12.3.2 Behavioral Biometrics |
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174 | (1) |
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12.4 Types of Biometric Systems |
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175 | (1) |
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12.5 Biometrics System Performance: False Acceptance and False Rejection |
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175 | (2) |
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177 | (1) |
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12.7 Performance Enhancement of Biometrics Systems |
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177 | (1) |
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12.8 Applications of Biometrics |
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178 | (1) |
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179 | (1) |
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179 | (2) |
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181 | (8) |
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13.1 Introduction: Background and Driving Forces |
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181 | (1) |
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13.2 Cybersecurity Tools and Methods |
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181 | (6) |
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13.2.1 Wire-shark--A Packet Sniffing and Packet Capturing Tool |
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182 | (3) |
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13.2.2 Autopsy--A Packet Sniffing and Packet Capturing Tool |
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185 | (1) |
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13.2.2.1 Download and Installation |
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185 | (1) |
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13.2.2.2 Features and Working |
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186 | (1) |
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13.2.2.3 Advantages of Using Autopsy |
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187 | (1) |
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187 | (1) |
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188 | (1) |
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14 Introduction to Optimization Algorithms-Bio Inspired |
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189 | (12) |
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189 | (1) |
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14.2 Evolutionary Algorithms (EA) |
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189 | (1) |
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190 | (2) |
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192 | (2) |
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194 | (3) |
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14.5.1 Genetic Programming Algorithm |
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195 | (1) |
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14.5.2 Basic Terminology Used in Genetic Programming |
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196 | (1) |
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14.5.3 Advantages of Genetic Programming over Genetic Algorithms |
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196 | (1) |
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14.6 Particle Swarm C)ptimization (PSO) |
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197 | (2) |
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14.7 Comparison": Genetic Algorithm, Genetic Programming and Particle Swarm Optimization |
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199 | (1) |
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200 | (1) |
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200 | (1) |
Appendix |
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201 | (2) |
Index |
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203 | |