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Diffstat (limited to 'app.R')
| -rw-r--r-- | app.R | 233 |
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@@ -0,0 +1,233 @@ +# +# This is a Shiny web application. You can run the application by clicking +# the 'Run App' button above. +# +# Find out more about building applications with Shiny here: +# +# http://shiny.rstudio.com/ +# +library(shinythemes) +library(shiny) +library(DT) +library(data.table) +library(ggplot2) +library(shinycssloaders) + + +# Defining Non Changing Variables +data <- fread("2020.10.01.csv") +data_na_removed <- na.omit(data) + +# Encoding the Label Column +# 1 - Benign 2 - Malicious 3 - Outlier +data_encoded <- data_na_removed +data_encoded$label <- factor(data_na_removed$label, + levels = c("benign", "malicious", "outlier"), + labels = c(1, 2, 3)) +data_encoded$label = as.numeric(data_encoded$label) +# Define Default Values +pch = 16 +features <- c("Average Input","Incoming Bytes","Outgoing Bytes", + "Destination IP", "Destination Port", "Entropy", + "Inbound Packets", "Outbound Packets", "Protocol", + "Source IP", "Source Port", "Start Time (s)", + "End Time (s)", "Total Entropy", "Type", "Duration") +feature_variables <- c("avg_ipt", "bytes_in", "bytes_out", "dest_ip", + "dest_port", "entropy", "num_pkts_out", "num_pkts_in", + "proto", "src_ip", "src_port", "time_end", "time_start", + "total_entropy", "label", "duration") + +# Define Elementary Functions +get_color <- function(a = 1) { + return(alpha("#e95420", a)) +} + +# Define UI for application +ui <- fluidPage( + theme = shinytheme("united"), + # Application title + titlePanel("A Comprehensive Approach To Analysis and Detection of Emerging + Threats due to Network Intrusion"), + + navbarPage( + "Network Intrusion Detection Demo", + tabPanel( + icon("home"), + p("Through this application, it is intended to develop a demo of a", + strong("Network Intrusion Detection System"), + "using different Machine Learning Techniques using the + LUFlow Network Intrusion Detection Data Set. This page is intended + to display the information about the dataset." + ,style="text-align:justify;color:black; + background-color:lavender;padding:15px;border-radius:10px"), + br(), + p("The data used in this application are publicly available on the", + em("LUFlow Network Intrusion Detection Data Set"), "Kaggle page. + The Data Set contains telemetry cap- tured using Cisco’s Joy tool. + This tool records multiple measurements asso- ciated with flows. + Features are engineered from these measurements, which are also + outlined below",style="text-align:justify;color:black; + background-color:papayawhip;padding:15px;border-radius:10px"), + hr(), + tags$style(".fa-database {color:#e95420}"), + h3(p(icon("database",lib = "font-awesome"), + em("Dataset Exploration "), + style="color:black;text-align:center")), + fluidRow(column(DT::dataTableOutput("renderData"), + width = 12)), + hr(), + p(em("Developed by"), br("Kumar Priyansh, Ritu Dimri, + Sandeep Perumalla, Hemanth Katikala"), + style="text-align:center; font-family: times") + ), + tabPanel( + "Data Visualization", + p("This part allows you to visualize features via different types of + plots. You can select whatever features you want to plot and hit + the \"Plot Graph\" button. Please keep in mind that all plots", + strong("might not be useful"), + "and you need to select which plots you want to visualize. If you + want to save an image of the currently visualized plot, please + right click on the plot and click on the relevant", + strong("save image"), + "option." + ,style="text-align:justify;color:black; + background-color:lavender;padding:15px;border-radius:10px"), + sidebarLayout( + sidebarPanel( + selectInput( + "plotType", + p("Type of Plot:"), + choices = c(Histogram = "hist", + "Scatter Plot" = "scatter", + "Mosaic Plot" = "mosaic") + ), + # Only show this panel if the plot type is a histogram + conditionalPanel( + condition = "input.plotType == 'hist'", + selectInput( + "plotVariable", + p("Feature to Visualize:"), + choices = features + ), + selectInput( + "plotVariant", + p("Plot Variant:"), + choices = c("Normal", "Log 10 Scale") + ) + ), + + # Only show this panel if the plot type is a scatter plot + conditionalPanel( + condition = "input.plotType == 'scatter'", + selectInput( + "plotVariable1", + p("First Feature to Visualize:"), + choices = features + ), + uiOutput("secondSelection") + ), + + # Single Mosiac Plot for now + conditionalPanel( + condition = "input.plotType == 'mosaic'", + selectInput( + "mosaicVariable", + p("Select Features to Visualize:"), + choices = c("Labels vs Protocols" = "labproto") + ) + ), + actionButton("plot", "Plot Graph", + width = "100%", icon = icon("chart-line"), + style="color: #fff; background-color: #e95420; + outline: none") + ), + mainPanel( + withSpinner( + plotOutput("selectedFeatureVariableForVisualization"), + type = 6, color = "#e95420" + ) + ) + ) + ), + tabPanel( + "Compare Models" + ) + ) +) + +# Define server logic +server <- function(input, output) { + output$renderData <- DT::renderDataTable( + DT::datatable({ + data_na_removed + }, + options = list( + initComplete = JS( + "function(settings, json) {", + "$(this.api().table().header()).css({'background-color': + 'moccasin', 'color': '1c1b1b'});", + "}"), + columnDefs=list(list(className='dt-center',targets="_all"))), + style = 'bootstrap', + class = 'cell-border stripe', + rownames = FALSE, + colnames = features) + ) + + output$secondSelection <- renderUI({ + selectedFeature <- input$plotVariable1 + selectInput( + "plotVariable2", + p("Second Feature to Visualize:"), + choices = features[!features %in% selectedFeature] + ) + }) + + output$selectedFeatureVariableForVisualization <- renderPlot({ + input$plot + isolate({ + plotType <- input$plotType + if (plotType == 'hist') { + selectedFeature <- input$plotVariable + plotVariant <- input$plotVariant + positionInFeatureArray <- which(features == selectedFeature) + selectedFeatureVariable <- feature_variables[positionInFeatureArray] + if (plotVariant == "Normal") { + hist(data_encoded[[selectedFeatureVariable]], + main = paste("Histogram Plot of", selectedFeature, sep = " ", collapse = NULL), + ylab = "Frequency", xlab = selectedFeature, + col = get_color(), pch = pch) + } else { + nonZeroSelectedFeature = data_encoded[data_encoded[[selectedFeatureVariable]] > 0] + hist(log(nonZeroSelectedFeature[[selectedFeatureVariable]]), + main = paste("Log 10 Base Histogram Plot of", selectedFeature, sep = " ", collapse = NULL), + ylab = "Frequency", xlab = selectedFeature, + col = get_color(), pch = pch) + } + } else if (plotType == 'scatter') { + firstFeature <- feature_variables[which(features == + input$plotVariable1)] + secondFeature <- feature_variables[which(features == + input$plotVariable2)] + try(plot(data_encoded[[firstFeature]], data_encoded[[secondFeature]], + main = paste("Scatter Plot of", input$plotVariable1, + "vs", input$plotVariable2, sep = " ", collapse = NULL), + ylab = input$plotVariable2, xlab = input$plotVariable1, + col = get_color(0.02), + pch = 16,), silent = TRUE) + } else { + selectedFeatures <- input$mosaicVariable + if (selectedFeatures == 'labproto') { + proto_label_mosaic <- table(data_encoded$proto, data_encoded$label) + mosaicplot(~ factor(proto)+factor(label, labels=c("benign","malicious","outlier")), + data = data_encoded,xlab = "Protocol", ylab = "Category", + main= "Mosaic plot of Protocol vs Category",shade = TRUE) + } + } + }) + }) +} + +# Run the application +shinyApp(ui = ui, server = server) |