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E-raamat: Global Cyber-Vulnerability Report

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This is the first book that uses cyber-vulnerability data to explore the vulnerability of over four million machines per year, covering a two-year period as reported by Symantec. Analyzing more than 20 billion telemetry reports comprising malware and binary reputation reports, this book quantifies the cyber-vulnerability of 44 countries for which at least 500 hosts were monitored.Chapters explain the context for this data and its impact, along with explaining how the cyber-vulnerability is calculated. This book also contains a detailed summary of the cyber-vulnerability of dozens of nations according to the percentage of infected hosts and number of infections. It identifies relationships between piracy rates, GDP and other country indicators. The book contains detailed information about potential cyber-security policies that 44 countries have announced, as well as an analysis of gaps in cyber-security policies in general.The Global Cyber-Vulnerability Report targets researche

rs and professionals including government and military workers, policy-makers and law-makers working in cybersecurity or the web intelligence fields. Advanced-level students in computer science will also find this report valuable as a reference.

Introduction.- Types of Malware and Malware Distribution Strategies.- Methodology and Measurement.- Human Behavior and Susceptibility to Cyber-Attacks.- Country by Country Analysis.
1 Introduction
1(32)
1.1 Data and Methodology
4(1)
1.2 The World's Most Cyber-Vulnerable Countries
5(4)
1.3 The Relationship Between Cyber-Attacks and GDP
9(2)
1.4 The Relationship between Cyber-Attacks and the Human Development Index
11(2)
1.5 The Relationship between Cyber-Attacks and HDI Health Index
13(2)
1.6 The Relationship Between Cyber-Attacks and Education
15(2)
1.6.1 The Overall Education Index
16(1)
1.6.2 Combined Gross Enrollment in Education
17(1)
1.6.3 Expected Years of Schooling
17(1)
1.7 Is Software Piracy Relevant to Cyber-Risk?
17(2)
1.8 Some Related Work
19(3)
1.9 National Cybersecurity Policies: A Quick Summary
22(4)
1.10 Recommendations
26(4)
1.10.1 Citizen Education
26(1)
1.10.2 Building up a National Cyber-Defense Capability
27(1)
1.10.3 Building Up Timely Cybersecurity Legislation and Regulation
28(1)
1.10.4 International Cybersecurity Cooperation
29(1)
1.10.5 Cybersecurity Attack Forecasting
29(1)
1.11 Conclusion
30(3)
References
31(2)
2 Types of Malware and Malware Distribution Strategies
33(14)
2.1 Types of Malware
34(4)
2.1.1 Trojans
34(2)
2.1.2 Worms
36(1)
2.1.3 Viruses
37(1)
2.1.4 Other Forms of Malware
38(1)
2.2 Malware Distribution
38(2)
2.2.1 Drive-by-Downloads
39(1)
2.2.2 Email
39(1)
2.2.3 Network Intrusion
39(1)
2.2.4 Social Engineering
40(1)
2.2.5 Downloaders
40(1)
2.3 Business Models
40(2)
2.3.1 Click Fraud
41(1)
2.3.2 Keyloggers
41(1)
2.3.3 Spam
41(1)
2.4 Cross-Country Studies
42(1)
2.5 Conclusion
43(4)
References
44(3)
3 Methodology and Measurement
47(22)
3.1 Research Question
47(1)
3.2 Data
47(1)
3.3 Dependent Variables
48(2)
3.4 Features
50(3)
3.4.1 Host-Based Features
50(2)
3.4.2 Macro-Economic Features
52(1)
3.5 Data Preparation
53(1)
3.6 Data Analysis
53(16)
3.6.1 Time-Series Analysis of Attacks
54(1)
3.6.2 Macro Economic Factors
54(4)
3.6.3 Host-Based Factors
58(1)
3.6.4 Percentage of Downloaded Binaries and Risk
58(3)
3.6.5 Percentage Low Prevalence Binary and Risk
61(1)
3.6.6 Percentage Unsigned Binaries and Risk
61(1)
3.6.7 Attacks of Misleading Applications and Spy ware
61(3)
3.6.8 Country Similarity by Host-Based Features
64(1)
3.6.9 Multivariate Analysis
65(2)
References
67(2)
4 Human Behavior and Susceptibility to Cyber-Attacks
69(24)
4.1 Introduction
69(2)
4.2 Dataset and Set-up
71(3)
4.2.1 Problem Statement
72(1)
4.2.2 The WINE Datasets
72(2)
4.3 Feature Construction
74(2)
4.4 User Classification
76(2)
4.5 User Behavior and Cyber-Attacks
78(11)
4.5.1 Analysis Methods
79(1)
4.5.2 Number of Binaries and Risk
80(1)
4.5.3 Percentage of Low/High Prevalence and Unique Binaries and Risk
81(4)
4.5.4 Percentage of Unsigned Binaries and Risk
85(1)
4.5.5 Percentage of Downloaded Binaries and Risk
86(2)
4.5.6 User Travel History and Risk
88(1)
4.6 Related Work
89(1)
4.7 Discussion and Conclusion
90(3)
References
91(2)
5 Country by Country Analysis
93(200)
5.1 Argentina
94(4)
5.2 Australia
98(5)
5.3 Austria
103(6)
5.4 Belgium
109(2)
5.5 Brazil
111(7)
5.6 Canada
118(4)
5.7 Chile
122(4)
5.8 China
126(5)
5.9 Colombia
131(4)
5.10 Czech Republic
135(5)
5.11 Denmark
140(4)
5.12 Finland
144(6)
5.13 France
150(3)
5.14 Germany
153(5)
5.15 Greece
158(3)
5.16 Hong Kong
161(5)
5.17 India
166(5)
5.18 Ireland
171(4)
5.19 Israel
175(5)
5.20 Italy
180(4)
5.21 Japan
184(6)
5.22 Malaysia
190(4)
5.23 Mexico
194(3)
5.24 Netherlands
197(5)
5.25 New Zealand
202(4)
5.26 Norway
206(5)
5.27 Philippines
211(4)
5.28 Poland
215(5)
5.29 Portugal
220(4)
5.30 Puerto Rico
224(3)
5.31 Russia
227(5)
5.32 Saudi Arabia
232(6)
5.33 Singapore
238(3)
5.34 South Africa
241(5)
5.35 South Korea
246(4)
5.36 Spain
250(4)
5.37 Sweden
254(3)
5.38 Switzerland
257(5)
5.39 Taiwan
262(4)
5.40 Thailand
266(4)
5.41 Turkey
270(4)
5.42 United Arab Emirates
274(4)
5.43 United Kingdom
278(5)
5.44 United States
283(10)
References
288(5)
Index 293