diff --git a/ISO27001effectiveness/R/Hackmageddon_Parser.R b/ISO27001effectiveness/R/Hackmageddon_Parser.R
index 9149bac..e0afb8c 100644
--- a/ISO27001effectiveness/R/Hackmageddon_Parser.R
+++ b/ISO27001effectiveness/R/Hackmageddon_Parser.R
@@ -74,6 +74,10 @@ ProcessHMRaw <- function(dataset.raw, dateOffset){
dataset$Country <- gsub("UAE","AE",dataset$Country)
dataset$Country <- gsub("CB","KH",dataset$Country)
+ CountryNames <- data.frame(countrycode::countrycode_data$country.name, countrycode::countrycode_data$iso2c, countrycode::countrycode_data$continent)
+ CountryNames <- setNames(CountryNames, c("Country_large","Country", "Continent"))
+ dataset <- merge(x = dataset, y = CountryNames, by = "Country", all.x = TRUE)
+ dataset <- dataset[!is.na(dataset$Continent),]
#Format properly the date
dataset$Date <- as.POSIXct(dataset$Date*86400, tz = "GMT", origin = dateOffset)
diff --git a/ISO27001effectiveness/R/ISOSurvey_Parser.R b/ISO27001effectiveness/R/ISOSurvey_Parser.R
index 92da800..09712cb 100644
--- a/ISO27001effectiveness/R/ISOSurvey_Parser.R
+++ b/ISO27001effectiveness/R/ISOSurvey_Parser.R
@@ -96,10 +96,12 @@ ProccesISOSurveyByCountryRaw <- function(dataset.raw, years){
#Translate country names to 2 letter code
- CountryNames <- data.frame(countrycode::countrycode_data$country.name, countrycode::countrycode_data$iso2c)
- CountryNames <- setNames(CountryNames, c("Country","country_short"))
+ CountryNames <- data.frame(countrycode::countrycode_data$country.name, countrycode::countrycode_data$iso2c, countrycode::countrycode_data$continent)
+ CountryNames <- setNames(CountryNames, c("Country","country_short", "Continent"))
dataset <- merge(x = dataset, y = CountryNames, by = "Country", all.x = TRUE)
+ dataset <- dataset[!is.na(dataset$Continent),]
+
dataset
}
diff --git a/ISO27001effectiveness/R/ReportGraphs.R b/ISO27001effectiveness/R/ReportGraphs.R
index 2caab8a..39c8bc0 100644
--- a/ISO27001effectiveness/R/ReportGraphs.R
+++ b/ISO27001effectiveness/R/ReportGraphs.R
@@ -7,12 +7,15 @@
#' @export
GetReportGraphs <- function(Cert_PerCountry,Attacks) {
#2012
- graph1 <- ggplot2::qplot(main = "Countries with above average number of companies certified with ISO 27001 (2012)",
+ graph1 <- ggplot2::qplot(main = "Countries with above average number of companies certified with 27001 (2012)",
x = reorder(country_short,X2012),
y = X2012,
xlab = "Country",
ylab = "Number of certifications",
- data = Cert_PerCountry[Cert_PerCountry$X2012 > mean(Cert_PerCountry$X2012),])
+ data = Cert_PerCountry[Cert_PerCountry$X2012 > mean(Cert_PerCountry$X2012),],
+ geom = "col",
+ fill = Continent)
+
attacks2k12 <- Attacks[Attacks$Date < "2013-01-01" & Attacks$Date >= "2012-01-01",]
frameAttacks2k12 <- as.data.frame(table(attacks2k12$Country))
colnames(frameAttacks2k12) <- c("Country","Attacks")
@@ -21,7 +24,9 @@ GetReportGraphs <- function(Cert_PerCountry,Attacks) {
y = Attacks,
xlab = "Country",
ylab = "Number of attacks",
- data = frameAttacks2k12[frameAttacks2k12$Attacks > mean(frameAttacks2k12$Attacks),])
+ data = frameAttacks2k12[frameAttacks2k12$Attacks > mean(frameAttacks2k12$Attacks),],
+ geom = "col",
+ fill = Continent)
Attacks2012ByMonth <- mutate(attacks2k12, month = format(attacks2k12$Date, "%m")) %>% group_by(month)
Attack2012FreqByMonth <- as.data.frame(table(Attacks2012ByMonth$month))
@@ -35,12 +40,14 @@ GetReportGraphs <- function(Cert_PerCountry,Attacks) {
xlab = "Month") + ggplot2::scale_x_continuous(breaks = 1:12)
#2013
- graph4 <- ggplot2::qplot(main = "Countries with above average number of companies certified with ISO 27001 (2013)",
+ graph4 <- ggplot2::qplot(main = "Countries with above average number of companies certified with 27001 (2013)",
x = reorder(country_short,X2013),
y = X2013,
xlab = "Country",
ylab = "Number of certifications",
- data = Cert_PerCountry[Cert_PerCountry$X2013 > mean(Cert_PerCountry$X2013),])
+ data = Cert_PerCountry[Cert_PerCountry$X2013 > mean(Cert_PerCountry$X2013),]
+ , geom = "col",
+ fill = Continent)
attacks2k13 <- Attacks[Attacks$Date < "2014-01-01" & Attacks$Date >= "2013-01-01",]
frameAttacks2k13 <- as.data.frame(table(attacks2k13$Country))
colnames(frameAttacks2k13) <- c("Country","Attacks")
@@ -49,7 +56,9 @@ GetReportGraphs <- function(Cert_PerCountry,Attacks) {
y = Attacks,
xlab = "Country",
ylab = "Number of attacks",
- data = frameAttacks2k13[frameAttacks2k13$Attacks > mean(frameAttacks2k13$Attacks),])
+ data = frameAttacks2k13[frameAttacks2k13$Attacks > mean(frameAttacks2k13$Attacks),]
+ , geom = "col",
+ fill = Continent)
Attacks2013ByMonth <- mutate(attacks2k13, month = format(attacks2k13$Date, "%m")) %>% group_by(month)
Attack2013FreqByMonth <- as.data.frame(table(Attacks2013ByMonth$month))
@@ -63,12 +72,14 @@ GetReportGraphs <- function(Cert_PerCountry,Attacks) {
xlab = "Month") + ggplot2::scale_x_continuous(breaks = 1:12)
#2014
- graph7 <- ggplot2::qplot(main = "Countries with above average number of companies certified with ISO 27001 (2014)",
+ graph7 <- ggplot2::qplot(main = "Countries with above average number of companies certified with 27001 (2014)",
x = reorder(country_short,X2014),
y = X2014,
xlab = "Country",
ylab = "Number of certifications",
- data = Cert_PerCountry[Cert_PerCountry$X2014 > mean(Cert_PerCountry$X2014),])
+ data = Cert_PerCountry[Cert_PerCountry$X2014 > mean(Cert_PerCountry$X2014),]
+ , geom = "col",
+ fill = Continent)
attacks2k14 <- Attacks[Attacks$Date < "2015-01-01" & Attacks$Date >= "2014-01-01",]
frameAttacks2k14 <- as.data.frame(table(attacks2k14$Country))
colnames(frameAttacks2k14) <- c("Country","Attacks")
@@ -77,7 +88,9 @@ GetReportGraphs <- function(Cert_PerCountry,Attacks) {
y = Attacks,
xlab = "Country",
ylab = "Number of attacks",
- data = frameAttacks2k14[frameAttacks2k14$Attacks > mean(frameAttacks2k14$Attacks),])
+ data = frameAttacks2k14[frameAttacks2k14$Attacks > mean(frameAttacks2k14$Attacks),]
+ , geom = "col",
+ fill = Continent)
Attacks2014ByMonth <- mutate(attacks2k14, month = format(attacks2k14$Date, "%m")) %>% group_by(month)
Attack2014FreqByMonth <- as.data.frame(table(Attacks2014ByMonth$month))
@@ -91,12 +104,14 @@ GetReportGraphs <- function(Cert_PerCountry,Attacks) {
xlab = "Month") + ggplot2::scale_x_continuous(breaks = 1:12)
#2015
- graph10 <- ggplot2::qplot(main = "Countries with above average number of companies certified with ISO 27001 (2015)",
+ graph10 <- ggplot2::qplot(main = "Countries with above average number of companies certified with 27001 (2015)",
x = reorder(country_short,X2015),
y = X2015,
xlab = "Country",
ylab = "Number of certifications",
- data = Cert_PerCountry[Cert_PerCountry$X2015 > mean(Cert_PerCountry$X2015),])
+ data = Cert_PerCountry[Cert_PerCountry$X2015 > mean(Cert_PerCountry$X2015),]
+ , geom = "col",
+ fill = Continent)
attacks2k15 <- Attacks[Attacks$Date < "2016-01-01" & Attacks$Date >= "2015-01-01",]
frameAttacks2k15 <- as.data.frame(table(attacks2k15$Country))
colnames(frameAttacks2k15) <- c("Country","Attacks")
@@ -105,7 +120,9 @@ GetReportGraphs <- function(Cert_PerCountry,Attacks) {
y = Attacks,
xlab = "Country",
ylab = "Number of attacks",
- data = frameAttacks2k15[frameAttacks2k15$Attacks > mean(frameAttacks2k15$Attacks),])
+ data = frameAttacks2k15[frameAttacks2k15$Attacks > mean(frameAttacks2k15$Attacks),]
+ , geom = "col",
+ fill = Continent)
Attacks2015ByMonth <- mutate(attacks2k15, month = format(attacks2k15$Date, "%m")) %>% group_by(month)
Attack2015FreqByMonth <- as.data.frame(table(Attacks2015ByMonth$month))
diff --git a/ISO27001effectiveness/Report.Rmd b/ISO27001effectiveness/Report.Rmd
index 0c7683e..70bc41c 100644
--- a/ISO27001effectiveness/Report.Rmd
+++ b/ISO27001effectiveness/Report.Rmd
@@ -1,9 +1,11 @@
---
title: "ISO 27001 Effectiveness"
-output: html_document
+output:
+ html_document: default
+ pdf_document: default
---
-```{r setup, include=FALSE}
+```{r setup, include=TRUE}
knitr::opts_chunk$set(echo = TRUE)
library(ISO27001effectiveness)
library(xlsx)
diff --git a/ISO27001effectiveness/Report.html b/ISO27001effectiveness/Report.html
index a57db60..6df7420 100644
--- a/ISO27001effectiveness/Report.html
+++ b/ISO27001effectiveness/Report.html
@@ -120,6 +120,32 @@ $(document).ready(function () {
+knitr::opts_chunk$set(echo = TRUE)
+library(ISO27001effectiveness)
+library(xlsx)
+## Loading required package: rJava
+## Loading required package: xlsxjars
+library(ggplot2)
+library(dplyr)
+##
+## Attaching package: 'dplyr'
+## The following objects are masked from 'package:stats':
+##
+## filter, lag
+## The following objects are masked from 'package:base':
+##
+## intersect, setdiff, setequal, union
+library(countrycode)
+
+source("./Main.R")
+## Scale for 'x' is already present. Adding another scale for 'x', which
+## will replace the existing scale.
+## Scale for 'x' is already present. Adding another scale for 'x', which
+## will replace the existing scale.
+## Scale for 'x' is already present. Adding another scale for 'x', which
+## will replace the existing scale.
+## Scale for 'x' is already present. Adding another scale for 'x', which
+## will replace the existing scale.
Abstract
La creciente preocupación de muchas empresas con infraestructura IT crítica frente a ciberataques ha llevado a algunas de ellas a tomar medidas de seguridad como la creación de departamentos de Seguridad de la Información, llevar a cabo auditorías de seguridad y obtener certificaciones de seguridad entre otras.