Data_Breach_Report_Clark_Xu.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "id": "eacd9370",
      "metadata": {
        "id": "eacd9370"
      },
      "source": [
        "# 1 Load Packages"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "3311c487",
      "metadata": {
        "scrolled": false,
        "id": "3311c487"
      },
      "outputs": [],
      "source": [
        "conda install -c conda-forge wordcloud"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "f8ca1507",
      "metadata": {
        "id": "f8ca1507"
      },
      "outputs": [],
      "source": [
        "import re\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.dates as mdates\n",
        "import matplotlib.image as mpimg\n",
        "from wordcloud import WordCloud\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "7c194985",
      "metadata": {
        "id": "7c194985"
      },
      "outputs": [],
      "source": [
        "# Surpress Scientific Notation\n",
        "pd.options.display.float_format = '{:.2f}'.format"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "2a0f9901",
      "metadata": {
        "id": "2a0f9901"
      },
      "source": [
        "# 2 Load Data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "b34d21bf",
      "metadata": {
        "id": "b34d21bf"
      },
      "outputs": [],
      "source": [
        "# First two rows of csv describe the column\n",
        "data = pd.read_csv(\"Data Breaches - Raw Data.csv\",header=[0,1])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "4769269e",
      "metadata": {
        "id": "4769269e",
        "outputId": "60c405e8-a03d-4144-fae4-fcf9af736c52"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Rows: 339, Columns: 14\n"
          ]
        }
      ],
      "source": [
        "# Check rows, columns\n",
        "dim = data.shape\n",
        "(rowCount,colCount) = dim\n",
        "\n",
        "# Return shape\n",
        "txt = \"Rows: {rows}, Columns: {cols}\"\n",
        "print(txt.format(rows=rowCount,cols=colCount))"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "5271aca2",
      "metadata": {
        "id": "5271aca2"
      },
      "source": [
        "# 3 Data Description"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "fabb1980",
      "metadata": {
        "scrolled": false,
        "id": "fabb1980"
      },
      "outputs": [],
      "source": [
        "# Remove Extra Symbols\n",
        "data.rename(columns=lambda x: re.sub('\\n', '; ', x.strip()),inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "8bd5c561",
      "metadata": {
        "scrolled": false,
        "id": "8bd5c561",
        "outputId": "0b133132-300f-4905-cf05-e5197a1a50d5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 339 entries, 0 to 338\n",
            "Data columns (total 14 columns):\n",
            " #   Column                                                                                                                                                                  Non-Null Count  Dtype  \n",
            "---  ------                                                                                                                                                                  --------------  -----  \n",
            " 0   (Entity, Unnamed: 0_level_1)                                                                                                                                            339 non-null    object \n",
            " 1   (alternative name, Unnamed: 1_level_1)                                                                                                                                  136 non-null    object \n",
            " 2   (records lost, Unnamed: 2_level_1)                                                                                                                                      338 non-null    object \n",
            " 3   (YEAR, year story broke)                                                                                                                                                339 non-null    int64  \n",
            " 4   (story, Unnamed: 4_level_1)                                                                                                                                             339 non-null    object \n",
            " 5   (SECTOR, web; healthcare; app; retail; gaming; transport; financial; tech; government; telecoms; legal; media; academic; energy; military)                              339 non-null    object \n",
            " 6   (METHOD, poor security; hacked; oops!; lost device ; inside job)                                                                                                        339 non-null    object \n",
            " 7   (interesting story, Unnamed: 7_level_1)                                                                                                                                 69 non-null     object \n",
            " 8   (DATA SENSITIVITY, 1. Just email address/Online information ; 2 SSN/Personal details ; 3 Credit card information ; 4 Health & other personal records ; 5 Full details)  339 non-null    int64  \n",
            " 9   (DISPLAYED RECORDS, =IF(C3>100000000,C3,\"))                                                                                                                             32 non-null     object \n",
            " 10  (Unnamed: 10_level_0, Unnamed: 10_level_1)                                                                                                                              0 non-null      float64\n",
            " 11  (source name, Unnamed: 11_level_1)                                                                                                                                      339 non-null    object \n",
            " 12  (1st source link, Unnamed: 12_level_1)                                                                                                                                  339 non-null    object \n",
            " 13  (2nd source link, Unnamed: 13_level_1)                                                                                                                                  32 non-null     object \n",
            "dtypes: float64(1), int64(2), object(11)\n",
            "memory usage: 37.2+ KB\n"
          ]
        }
      ],
      "source": [
        "# Column Headers and Data Types\n",
        "data.info()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "37be135a",
      "metadata": {
        "id": "37be135a",
        "outputId": "c948d186-9777-40c4-b7fb-20bf3b9bac65"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Entity</th>\n",
              "      <th>alternative name</th>\n",
              "      <th>records lost</th>\n",
              "      <th>YEAR</th>\n",
              "      <th>story</th>\n",
              "      <th>SECTOR</th>\n",
              "      <th>METHOD</th>\n",
              "      <th>interesting story</th>\n",
              "      <th>DATA SENSITIVITY</th>\n",
              "      <th>DISPLAYED RECORDS</th>\n",
              "      <th>Unnamed: 10_level_0</th>\n",
              "      <th>source name</th>\n",
              "      <th>1st source link</th>\n",
              "      <th>2nd source link</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0_level_1</th>\n",
              "      <th>Unnamed: 1_level_1</th>\n",
              "      <th>Unnamed: 2_level_1</th>\n",
              "      <th>year story broke</th>\n",
              "      <th>Unnamed: 4_level_1</th>\n",
              "      <th>web; healthcare; app; retail; gaming; transport; financial; tech; government; telecoms; legal; media; academic; energy; military</th>\n",
              "      <th>poor security; hacked; oops!; lost device ; inside job</th>\n",
              "      <th>Unnamed: 7_level_1</th>\n",
              "      <th>1. Just email address/Online information ; 2 SSN/Personal details ; 3 Credit card information ; 4 Health &amp; other personal records ; 5 Full details</th>\n",
              "      <th>=IF(C3&gt;100000000,C3,\")</th>\n",
              "      <th>Unnamed: 10_level_1</th>\n",
              "      <th>Unnamed: 11_level_1</th>\n",
              "      <th>Unnamed: 12_level_1</th>\n",
              "      <th>Unnamed: 13_level_1</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>US Customs and Border Protection</td>\n",
              "      <td>NaN</td>\n",
              "      <td>100,000</td>\n",
              "      <td>2019</td>\n",
              "      <td>June 2019. Photos of travellers' faces and lic...</td>\n",
              "      <td>government</td>\n",
              "      <td>hacked</td>\n",
              "      <td>y</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Washington Post</td>\n",
              "      <td>https://www.washingtonpost.com/technology/2019...</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                             Entity   alternative name       records lost  \\\n",
              "                 Unnamed: 0_level_1 Unnamed: 1_level_1 Unnamed: 2_level_1   \n",
              "0  US Customs and Border Protection                NaN            100,000   \n",
              "\n",
              "              YEAR                                              story  \\\n",
              "  year story broke                                 Unnamed: 4_level_1   \n",
              "0             2019  June 2019. Photos of travellers' faces and lic...   \n",
              "\n",
              "                                                                                                                            SECTOR  \\\n",
              "  web; healthcare; app; retail; gaming; transport; financial; tech; government; telecoms; legal; media; academic; energy; military   \n",
              "0                                         government                                                                                 \n",
              "\n",
              "                                                  METHOD  interesting story  \\\n",
              "  poor security; hacked; oops!; lost device ; inside job Unnamed: 7_level_1   \n",
              "0                                             hacked                      y   \n",
              "\n",
              "                                                                                                                                    DATA SENSITIVITY  \\\n",
              "  1. Just email address/Online information ; 2 SSN/Personal details ; 3 Credit card information ; 4 Health & other personal records ; 5 Full details   \n",
              "0                                                  2                                                                                                   \n",
              "\n",
              "       DISPLAYED RECORDS Unnamed: 10_level_0         source name  \\\n",
              "  =IF(C3>100000000,C3,\") Unnamed: 10_level_1 Unnamed: 11_level_1   \n",
              "0                    NaN                 NaN     Washington Post   \n",
              "\n",
              "                                     1st source link     2nd source link  \n",
              "                                 Unnamed: 12_level_1 Unnamed: 13_level_1  \n",
              "0  https://www.washingtonpost.com/technology/2019...                 NaN  "
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Example Row\n",
        "data.head(1)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "0b143236",
      "metadata": {
        "id": "0b143236"
      },
      "source": [
        "# 4 Data Cleaning and Validation"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "02ab5c4d",
      "metadata": {
        "id": "02ab5c4d"
      },
      "source": [
        "## Cleaning Columns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "4690a52d",
      "metadata": {
        "id": "4690a52d"
      },
      "outputs": [],
      "source": [
        "# Remove Empty Column\n",
        "\n",
        "## Get index of null columns\n",
        "nulls = data.isna().sum()\n",
        "nullsIx = [ix for ix,i in enumerate(nulls.index) if (nulls[i] == rowCount)]\n",
        "\n",
        "## Remove null columns by index\n",
        "data.drop(data.columns[nullsIx],axis=1,inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a8df7260",
      "metadata": {
        "id": "a8df7260"
      },
      "outputs": [],
      "source": [
        "# Clean Headers\n",
        "\n",
        "## Fix Empty Headers\n",
        "data.rename(columns=lambda x: re.sub('Unnamed.*_1', '', x.strip()),inplace=True)\n",
        "\n",
        "## Fix Capitalization\n",
        "data.rename(columns=lambda x: x.title(),inplace=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "a3b4a5ab",
      "metadata": {
        "scrolled": false,
        "id": "a3b4a5ab",
        "outputId": "f20867e0-4730-4053-deef-6f4abb6a69cd"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Entity</th>\n",
              "      <th>Alternative Name</th>\n",
              "      <th>Records Lost</th>\n",
              "      <th>Year</th>\n",
              "      <th>Story</th>\n",
              "      <th>Sector</th>\n",
              "      <th>Method</th>\n",
              "      <th>Interesting Story</th>\n",
              "      <th>Data Sensitivity</th>\n",
              "      <th>Displayed Records</th>\n",
              "      <th>Source Name</th>\n",
              "      <th>1St Source Link</th>\n",
              "      <th>2Nd Source Link</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>Year Story Broke</th>\n",
              "      <th></th>\n",
              "      <th>Web; Healthcare; App; Retail; Gaming; Transport; Financial; Tech; Government; Telecoms; Legal; Media; Academic; Energy; Military</th>\n",
              "      <th>Poor Security; Hacked; Oops!; Lost Device ; Inside Job</th>\n",
              "      <th></th>\n",
              "      <th>1. Just Email Address/Online Information ; 2 Ssn/Personal Details ; 3 Credit Card Information ; 4 Health &amp; Other Personal Records ; 5 Full Details</th>\n",
              "      <th>=If(C3&gt;100000000,C3,\")</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [(Entity, ), (Alternative Name, ), (Records Lost, ), (Year, Year Story Broke), (Story, ), (Sector, Web; Healthcare; App; Retail; Gaming; Transport; Financial; Tech; Government; Telecoms; Legal; Media; Academic; Energy; Military), (Method, Poor Security; Hacked; Oops!; Lost Device ; Inside Job), (Interesting Story, ), (Data Sensitivity, 1. Just Email Address/Online Information ; 2 Ssn/Personal Details ; 3 Credit Card Information ; 4 Health & Other Personal Records ; 5 Full Details), (Displayed Records, =If(C3>100000000,C3,\")), (Source Name, ), (1St Source Link, ), (2Nd Source Link, )]\n",
              "Index: []"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Check Headers\n",
        "data.head(0)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "7e91e8a9",
      "metadata": {
        "id": "7e91e8a9"
      },
      "source": [
        "## Cleaning Rows"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "dac1bd08",
      "metadata": {
        "id": "dac1bd08",
        "outputId": "213afd30-d4fe-44f3-ce3e-6f4cd10bbcae"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "count          335.00\n",
              "mean      40444500.33\n",
              "std      144980789.89\n",
              "min           1025.00\n",
              "25%         475000.00\n",
              "50%        3000000.00\n",
              "75%       18000000.00\n",
              "max     1370000000.00\n",
              "Name: Records Lost, dtype: float64"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Convert Records Lost to Numeric\n",
        "\n",
        "## Remove Commas\n",
        "data['Records Lost'] = data['Records Lost'].replace(',','',regex=True)\n",
        "\n",
        "## Story seems to have data quality issue when reporting ALL records \n",
        "data['Records Lost'] = data['Records Lost'].replace('ALL','',regex=True)\n",
        "\n",
        "# M stands for 1,000,000\n",
        "data['Records Lost'] = data['Records Lost'].replace('M','000000',regex=True)\n",
        "\n",
        "# An upper bound is an appropriate estimate\n",
        "data['Records Lost'] = data['Records Lost'].replace('<','',regex=True)\n",
        "\n",
        "# Run the conversion\n",
        "data['Records Lost'] = pd.to_numeric(data['Records Lost'], errors='coerce')\n",
        "\n",
        "# Check stats: record losses vary from 1 thousand to 137 billion\n",
        "data['Records Lost'].describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "1b8ce53d",
      "metadata": {
        "id": "1b8ce53d"
      },
      "outputs": [],
      "source": [
        "# Fix Sources\n",
        "\n",
        "## Guardian\n",
        "data['Source Name'] = data['Source Name'].replace('The Guardian','Guardian',regex=True)\n",
        "\n",
        "## NYTimes\n",
        "data['Source Name'] = data['Source Name'].replace('NYTimes','NY Times',regex=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "424b59ca",
      "metadata": {
        "id": "424b59ca"
      },
      "source": [
        "# 5 Data Mining"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "4a3799fe",
      "metadata": {
        "id": "4a3799fe"
      },
      "outputs": [],
      "source": [
        "# Clean Breach Size\n",
        "loss = data['Records Lost']\n",
        "lossCleaned = loss.dropna()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "aecfbc85",
      "metadata": {
        "scrolled": true,
        "id": "aecfbc85",
        "outputId": "0d397bc6-97c8-437e-84f0-ef55e31761bc"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "count          339\n",
              "unique         163\n",
              "top       Guardian\n",
              "freq            24\n",
              "Name: Source Name, dtype: object"
            ]
          },
          "execution_count": 14,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Investigate Source\n",
        "sources = data['Source Name']\n",
        "\n",
        "# We see that there \n",
        "sources.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "3f268a81",
      "metadata": {
        "id": "3f268a81"
      },
      "outputs": [],
      "source": [
        "# Get Top Sources\n",
        "sourceCounts = sources.value_counts().to_dict()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "2fac85f1",
      "metadata": {
        "scrolled": true,
        "id": "2fac85f1",
        "outputId": "6625625d-1507-4b28-f2d7-15fcb810e908"
      },
      "outputs": [
        {
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              "    .dataframe tbody tr th {\n",
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              "      <th>000</th>\n",
              "      <th>05</th>\n",
              "      <th>072</th>\n",
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              "      <th>1025</th>\n",
              "      <th>106</th>\n",
              "      <th>10gb</th>\n",
              "      <th>...</th>\n",
              "      <th>äôs</th>\n",
              "      <th>äù</th>\n",
              "      <th>a</th>\n",
              "      <th>clandestinely</th>\n",
              "      <th>clicking</th>\n",
              "      <th>compromised</th>\n",
              "      <th>data</th>\n",
              "      <th>downloads</th>\n",
              "      <th>sony</th>\n",
              "      <th>unauthorized</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
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              "      <th>0</th>\n",
              "      <td>0.00</td>\n",
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              "      <td>0.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1 rows × 2051 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "   000   05  072   10  100  1000  100m  1025  106  10gb  ...  äôs   äù    a  \\\n",
              "0 0.00 0.00 0.00 0.00 0.00  0.00  0.00  0.00 0.00  0.00  ... 0.00 0.00 0.00   \n",
              "\n",
              "   clandestinely  clicking  compromised  data  downloads  sony  unauthorized  \n",
              "0           0.00      0.00         0.00  0.00       0.00  0.00          0.00  \n",
              "\n",
              "[1 rows x 2051 columns]"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Get Top Search Terms in Story\n",
        "\n",
        "## Make Corpus\n",
        "corpus = data['Story']\n",
        "\n",
        "## Make Vectorizer in single English words\n",
        "vectorizer = TfidfVectorizer(stop_words='english', ngram_range = (1,1))\n",
        "\n",
        "## Apply Vectorizer\n",
        "X = vectorizer.fit_transform(corpus)\n",
        "\n",
        "## Get Search Terms\n",
        "feature_names = vectorizer.get_feature_names_out()\n",
        "\n",
        "## Convert Matrix to Dataframe\n",
        "dense = X.todense()\n",
        "denselist = dense.tolist()\n",
        "searchTerms = pd.DataFrame(denselist, columns=feature_names)\n",
        "\n",
        "# Clean Dataframe\n",
        "searchTerms.rename(columns=lambda x: re.sub('äú', '', x.strip()),inplace=True)\n",
        "searchTerms.head(1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "db2258aa",
      "metadata": {
        "scrolled": true,
        "id": "db2258aa",
        "outputId": "58c8484f-2bed-432b-e074-61351953e72f"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Records Lost</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>17.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>796994565.29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>1145098086.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1800000.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>88455500.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>232898177.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>1558750000.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>4071586578.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       Records Lost\n",
              "                   \n",
              "count         17.00\n",
              "mean   796994565.29\n",
              "std   1145098086.44\n",
              "min      1800000.00\n",
              "25%     88455500.00\n",
              "50%    232898177.00\n",
              "75%   1558750000.00\n",
              "max   4071586578.00"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Get Breaches Over Time\n",
        "\n",
        "## Multi-index Columns\n",
        "recordCol = ('Records Lost','')\n",
        "yearCol = ('Year','Year Story Broke')\n",
        "dataTime = data.loc[:, [yearCol,recordCol]]\n",
        "dataTime[yearCol] = dataTime[yearCol].astype(int)\n",
        "\n",
        "## Get total records lost per year\n",
        "breachTime = dataTime.groupby([yearCol]).sum()\n",
        "\n",
        "## Check stats: annual losses vary from 1.8 million to 1.5 billion\n",
        "breachTime.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "944cc825",
      "metadata": {
        "scrolled": true,
        "id": "944cc825",
        "outputId": "ebf90d94-01cf-4567-b0b3-7ec4f1252520"
      },
      "outputs": [
        {
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead tr th {\n",
              "        text-align: left;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th>Records Lost</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>17.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>33248176.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>33702157.81</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>703285.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>10126007.70</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>17824968.21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>51958333.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>98207652.36</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      Records Lost\n",
              "                  \n",
              "count        17.00\n",
              "mean   33248176.13\n",
              "std    33702157.81\n",
              "min      703285.67\n",
              "25%    10126007.70\n",
              "50%    17824968.21\n",
              "75%    51958333.33\n",
              "max    98207652.36"
            ]
          },
          "execution_count": 18,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Get average records lost per year\n",
        "breachAvg = dataTime.groupby([yearCol]).mean()\n",
        "\n",
        "# Check stats: average losses per breach vary from 703 thousand to 98.2 million\n",
        "breachAvg.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "ea84255e",
      "metadata": {
        "scrolled": false,
        "id": "ea84255e",
        "outputId": "9b27f7ea-0f45-492d-9589-26ca02212fe9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "count   24.00\n",
              "mean    14.12\n",
              "std     21.87\n",
              "min      1.00\n",
              "25%      1.00\n",
              "50%      4.00\n",
              "75%     17.00\n",
              "max     97.00\n",
              "Name: (Sector, Web; Healthcare; App; Retail; Gaming; Transport; Financial; Tech; Government; Telecoms; Legal; Media; Academic; Energy; Military), dtype: float64"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Get counts by sector\n",
        "sectorData = data.iloc[:,5]\n",
        "sectorCounts = sectorData.value_counts()\n",
        "\n",
        "# Check stats: Largest sector had 97 breaches and smallest sector had 1 breach\n",
        "sectorCounts.describe()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "3bc759a3",
      "metadata": {
        "id": "3bc759a3",
        "outputId": "96d88fa3-8e13-43da-cffb-63d68aa29bf2"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "count     5.00\n",
              "mean     67.80\n",
              "std      82.62\n",
              "min      19.00\n",
              "25%      20.00\n",
              "50%      39.00\n",
              "75%      47.00\n",
              "max     214.00\n",
              "Name: (Method, Poor Security; Hacked; Oops!; Lost Device ; Inside Job), dtype: float64"
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Get counts by method\n",
        "methodData = data.iloc[:,6]\n",
        "methodCounts = methodData.value_counts()\n",
        "\n",
        "# Check stats: Most common method was used 214 times and least common method was used 19 times\n",
        "methodCounts.describe()"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "63e76051",
      "metadata": {
        "id": "63e76051"
      },
      "source": [
        "# 6 Data Visualization"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "c259c701",
      "metadata": {
        "scrolled": true,
        "id": "c259c701",
        "outputId": "0e0ac168-3561-449b-f9a2-3285454083cb"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Visualize Breach Size\n",
        "\n",
        "## Set Plot Parameters\n",
        "fig1, ax1 = plt.subplots()\n",
        "ax1.set_title(\"Size Distribution of Data Breaches\")\n",
        "ax1.set_ylabel(\"Number of Breaches\")\n",
        "ax1.set_xlabel(\"Billions of Records Lost\")\n",
        "\n",
        "## Make Plot\n",
        "plt.hist(lossCleaned) \n",
        "plt.show()\n",
        "fig1.savefig(\"Image/breach.jpg\",bbox_inches = \"tight\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "15ee8634",
      "metadata": {
        "id": "15ee8634",
        "outputId": "f595a7e3-92d9-4ba1-8ee9-aeab4b9eaf52"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Visualize Top Sources\n",
        "\n",
        "## Filter to 3 or more occurrences\n",
        "sourceCountsFiltered = { key:value for (key,value) in sourceCounts.items() if (value >= 3)}\n",
        "\n",
        "## Set Plot Parameters\n",
        "fig2, ax2 = plt.subplots()\n",
        "ax2.set_title(\"Common Media Outlets for Data Breach Reporting\")\n",
        "plt.xticks(rotation=90)\n",
        "ax2.set_ylabel(\"Frequency\")\n",
        "\n",
        "## Make Plot\n",
        "plt.bar(range(len(sourceCountsFiltered)), list(sourceCountsFiltered.values()), align='center')\n",
        "plt.xticks(range(len(sourceCountsFiltered)), list(sourceCountsFiltered.keys()))\n",
        "plt.show()\n",
        "fig2.savefig(\"Image/source.jpg\",bbox_inches = \"tight\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "67398c28",
      "metadata": {
        "id": "67398c28"
      },
      "outputs": [],
      "source": [
        "# Word Cloud Helper Function\n",
        "\n",
        "def black_color_func(word, font_size, position,orientation,random_state=None, **kwargs):\n",
        "    \"\"\"\n",
        "    Change the value of words in word cloud to black\n",
        "    \"\"\"\n",
        "    return(\"hsl(0,100%, 1%)\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "90ef63c5",
      "metadata": {
        "scrolled": true,
        "id": "90ef63c5",
        "outputId": "bc513f6c-a5c4-4de7-ba03-ac2e513691e7"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Alternative Top Sources Visualization\n",
        "\n",
        "## Make Word Cloud\n",
        "wordcloud = WordCloud(font_path='/Library/Fonts/Arial Unicode.ttf',background_color=\"white\").generate_from_frequencies(sourceCountsFiltered)\n",
        "\n",
        "## Format Word Cloud\n",
        "fig3, ax3 = plt.subplots()\n",
        "ax3.set_title(\"Common Media Outlets for Data Breach Reporting\")\n",
        "plt.axis(\"off\")\n",
        "wordcloud.recolor(color_func = black_color_func)\n",
        "\n",
        "## Show Word Cloud\n",
        "plt.imshow(wordcloud, interpolation=\"bilinear\")\n",
        "fig3.savefig(\"Image/searchTerm.jpg\",bbox_inches = \"tight\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "01abc20f",
      "metadata": {
        "id": "01abc20f",
        "outputId": "0777c958-e6ee-4f47-b336-e291546b6b6f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f98711c7190>"
            ]
          },
          "execution_count": 25,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Top Search Terms Visualization in a Document\n",
        "\n",
        "## Prep Dataframe\n",
        "searchTermsIn = searchTerms.transpose()\n",
        "searchTermsIn.columns = data['Story']\n",
        "\n",
        "## Example Story\n",
        "story1 = data['Story'][0]\n",
        "\n",
        "## Format Word Cloud\n",
        "plt.title(\"Example Top Search Terms in Story\")\n",
        "plt.axis(\"off\")\n",
        "\n",
        "## Create Word Cloud\n",
        "wordcloud2 = WordCloud().generate_from_frequencies(searchTermsIn[story1])\n",
        "plt.imshow(wordcloud2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "33ab3a7a",
      "metadata": {
        "id": "33ab3a7a",
        "outputId": "74af5dcb-f408-4d56-ada2-6c4dfa52c191"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "<matplotlib.image.AxesImage at 0x7f9890d58e20>"
            ]
          },
          "execution_count": 26,
          "metadata": {},
          "output_type": "execute_result"
        },
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Top Search Terms Visualization for a Corpus\n",
        "\n",
        "## Make String\n",
        "allStory = data['Story'].str.cat(sep='')\n",
        "\n",
        "## Get Frequencies\n",
        "allWords = allStory.split()\n",
        "allWordsFreq = [allWords.count(w) for w in allWords]\n",
        "allWordsDict = dict(zip(allWords,allWordsFreq))\n",
        "\n",
        "## Format Word Cloud\n",
        "plt.title(\"Top Search Terms across all Stories\")\n",
        "plt.axis(\"off\")\n",
        "\n",
        "## Filter to 5 or more characters\n",
        "allWordsDictFiltered = { key:value for (key,value) in allWordsDict.items() if (len(key) >= 5)}\n",
        "\n",
        "## Create Word Cloud\n",
        "wordcloud3 = WordCloud().generate_from_frequencies(allWordsDictFiltered)\n",
        "plt.imshow(wordcloud3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "77d95905",
      "metadata": {
        "scrolled": true,
        "id": "77d95905",
        "outputId": "f25fef88-cb07-4010-f5a3-633ef0c0ffe0"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Total records lost are increasing about 147678146 records year-over-year\n"
          ]
        }
      ],
      "source": [
        "# Total Records Lost Over Time\n",
        "\n",
        "## Label Plot\n",
        "fig4, ax4 = plt.subplots()\n",
        "ax4.set_title(\"Total Records Lost in Data Breaches\")\n",
        "ax4.set_ylabel(\"Billions of Records Lost\")\n",
        "ax4.set_xlabel(\"Year\")\n",
        "\n",
        "## Format Plot\n",
        "plt.xticks(range(1999,2020))\n",
        "plt.xticks(rotation=90)\n",
        "\n",
        "## Make Regression\n",
        "x,y = list(breachTime.index), list(breachTime.iloc[:,0])\n",
        "coef = np.polyfit(x,y,1)\n",
        "poly1d_fn = np.poly1d(coef) \n",
        "\n",
        "## Make Plot\n",
        "plt.plot(breachTime,marker='o',ls='')\n",
        "plt.show()\n",
        "fig4.savefig(\"Image/total.jpg\",bbox_inches = \"tight\")\n",
        "\n",
        "txt = \"Total records lost are increasing about {slope} records year-over-year\"\n",
        "print(txt.format(slope=int(coef[0])))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "eca75f3c",
      "metadata": {
        "id": "eca75f3c",
        "outputId": "fb66e8ad-a64e-4648-edbd-38c08b7f5ff7"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Average records lost are increasing about 2821207 records year-over-year\n"
          ]
        }
      ],
      "source": [
        "# Average Records Lost Over Time\n",
        "\n",
        "## Label Plot\n",
        "plt.title(\"Average Records Lost in Data Breaches\")\n",
        "plt.ylabel(\"Billions of Records Lost\")\n",
        "plt.xlabel(\"Year\")\n",
        "\n",
        "## Format Plot\n",
        "plt.xticks(range(1999,2020))\n",
        "plt.xticks(rotation=90)\n",
        "\n",
        "## Make Regression\n",
        "x,y = list(breachAvg.index), list(breachAvg.iloc[:,0])\n",
        "coef = np.polyfit(x,y,1)\n",
        "poly1d_fn = np.poly1d(coef) \n",
        "\n",
        "## Make Plot\n",
        "plt.plot(breachAvg,marker='o',ls='')\n",
        "plt.show()\n",
        "\n",
        "txt = \"Average records lost are increasing about {slope} records year-over-year\"\n",
        "print(txt.format(slope=int(coef[0])))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "32453090",
      "metadata": {
        "id": "32453090",
        "outputId": "897c106c-9750-4909-cc35-ba01902cda85"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Other sectors: ['academic', 'transport', 'tech', 'media', 'tech, web', 'military', 'energy', 'tech, retail', 'government, healthcare', 'web, gaming', 'military, healthcare', 'legal', 'web, military', 'web, tech', 'tech, app', 'government, military']\n"
          ]
        }
      ],
      "source": [
        "# Visualize Sector\n",
        "\n",
        "## Aggregate Small Values\n",
        "sectorDict = sectorCounts.to_dict()\n",
        "sectorDictFiltered = {key:'other' for (key,value) in sectorDict.items() if (value <= 10)}\n",
        "otherSectors = sectorDictFiltered.keys()\n",
        "sectorCounts.rename(index=sectorDictFiltered,inplace=True)\n",
        "sectorCounts = sectorCounts.groupby(level=0).sum()\n",
        "\n",
        "## Make Pie\n",
        "fig5, ax5 = plt.subplots()\n",
        "ax5.set_title(\"Breakdown of Data Breaches by Sector\")\n",
        "plt.pie(sectorCounts,labels=sectorCounts.index,autopct='%1.0f%%')\n",
        "\n",
        "## Show Pie\n",
        "plt.show()\n",
        "fig5.savefig(\"Image/sectors.jpg\",bbox_inches = \"tight\")\n",
        "\n",
        "print(\"Other sectors:\",list(otherSectors))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "130c9eb3",
      "metadata": {
        "id": "130c9eb3",
        "outputId": "6c4f3013-7111-4bdc-b074-0991ceaa63a3"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Visualize Method\n",
        "\n",
        "## Make Pie\n",
        "fig6, ax6 = plt.subplots()\n",
        "ax6.set_title(\"Breakdown of Data Breaches by Method\")\n",
        "plt.pie(methodCounts,labels=methodCounts.index,autopct='%1.0f%%')\n",
        "\n",
        "## Show Pie\n",
        "plt.show()\n",
        "fig6.savefig(\"Image/methods.jpg\",bbox_inches = \"tight\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "91459a4d",
      "metadata": {
        "id": "91459a4d"
      },
      "outputs": [],
      "source": [
        "sectorDict = sectorCounts.to_dict()\n",
        "sectorDictFiltered = {key:'other' for (key,value) in sectorDict.items() if (value <= 10)}"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "0f67e386",
      "metadata": {
        "id": "0f67e386"
      },
      "source": [
        "# 7 Presenting Conclusions"
      ]
    },
    {
      "cell_type": "markdown",
      "id": "acc0979c",
      "metadata": {
        "id": "acc0979c"
      },
      "source": [
        "#### The typical record loss is about 3 million records, although this can vary between a thousand records and 1.37 billion. \n",
        "\n",
        "![image info](Images/breach.jpg)\n",
        "\n",
        "Note that record losses of less than 500 are not reportable to the media, and also less likely to be captured from web-crawling, so there is under-representation of the impact of smaller record losses."
      ]
    },
    {
      "cell_type": "markdown",
      "id": "30dcfb4e",
      "metadata": {
        "id": "30dcfb4e"
      },
      "source": [
        "#### Media coverage of data breaches occur most often on mainstream news sites such as Guardian, The Register, and BBC News.\n",
        "\n",
        "![image info](Images/source.jpg)\n",
        "\n",
        "Note that the dataset shows an overall bias towards English-language news media, with a slight bias towards British-English news media. Further work should look into more representation from other parts of the English-speaking world, as well as non-English speaking media such as Spanish, Russian, and so on."
      ]
    },
    {
      "cell_type": "markdown",
      "id": "39148c9b",
      "metadata": {
        "id": "39148c9b"
      },
      "source": [
        "#### The most common search terms in media stories involving data breaches include names, numbers, and addresses.\n",
        "\n",
        "![image info](Images/searchTerm.jpg)\n",
        "\n",
        "Also common are boilerplate words such as million, information, details, which we may want to remove from the natural language processing."
      ]
    },
    {
      "cell_type": "markdown",
      "id": "2400f6f2",
      "metadata": {
        "id": "2400f6f2"
      },
      "source": [
        "#### Both the total number of records lost and the average number of records lost per breach are increasing year-over-year. Total number of records lost are increasing about 147 million records year-over-year. Average number of records lost per data breach are increasing about 282 thousand records year-over-year.\n",
        "\n",
        "![image info](Images/total.jpg)\n",
        "\n",
        "However, we should be careful about the recency effect. More recent breaches may be better documented, which can increase the reported number of records lost in recent years. Furthermore, the number of breach stories in the dataset is a few hundred, and further study with a larger number of breach stories on the order of a few thousand is needed to better illuminate this trend."
      ]
    },
    {
      "cell_type": "markdown",
      "id": "91171907",
      "metadata": {
        "id": "91171907"
      },
      "source": [
        "#### The most common sectors to experience data breaches are internet, healthcare, government, and financial institutions.\n",
        "\n",
        "![image info](Images/sectors.jpg)\n",
        "\n",
        "Some of the less common sectors for data breaches include energy, gaming, and academic institutions. Furthermore, if a sector did not report any breaches then it would not be included in the analysis."
      ]
    },
    {
      "cell_type": "markdown",
      "id": "3a692a5b",
      "metadata": {
        "id": "3a692a5b"
      },
      "source": [
        "#### The most common hacking methods were lost devices and insider threats, although the vast majority of hacking methods are unknown.\n",
        "\n",
        "![image info](Images/methods.jpg)\n",
        "\n",
        "For institutions that had poor security or were hacked, additional information is needed to specify the hacking method employed in the attack."
      ]
    },
    {
      "cell_type": "markdown",
      "id": "baeff569",
      "metadata": {
        "id": "baeff569"
      },
      "source": [
        "### End of Notebook"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
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