lanl_netflow_activity.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://csr.lanl.gov/data/2017.html\n",
    "\n",
    "\n",
    "https://csr.lanl.gov/data-fence/1571548765/1fcFh-bNWqPJuUSQe72Z9N_Nw28=/unified-host-network-dataset-2017/netflow.html"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compressed, netflow_day-02.bz2 is 1100MB\n",
    "\n",
    "Extracts to 6.7GB; that's 115,949,436 lines"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "!bzip2 -d netflow_day-02.bz2 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pandas 0.23.4\n",
      "networkx 2.2\n"
     ]
    }
   ],
   "source": [
    "import pandas\n",
    "print('pandas',pandas.__version__)\n",
    "import networkx\n",
    "print('networkx',networkx.__version__)\n",
    "from networkx import nx\n",
    "from matplotlib import pyplot as plt\n",
    "import time\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Time: The start time of the event in epoch time format\n",
    "* Duration: The duration of the event in seconds.\n",
    "* SrcDevice: The device that likely initiated the event.\n",
    "* DstDevice: The receiving device.\n",
    "* Protocol: The protocol number.\n",
    "* SrcPort: The port used by the SrcDevice.\n",
    "* DstPort: The port used by the DstDevice.\n",
    "* SrcPackets: The number of packets the SrcDevice sent during the event.\n",
    "* DstPackets: The number of packets the DstDevice sent during the event.\n",
    "* SrcBytes: The number of bytes the SrcDevice sent during the event.\n",
    "* DstBytes: The number of bytes the DstDevice sent during the event."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "start_time = time.time()\n",
    "nfdf = pandas.read_csv('netflow_day-02',\n",
    "                       nrows=1000000, \n",
    "                       names=['Time','Duration','SrcDevice','DstDevice','Protocol','SrcPort','DstPort','SrcPackets','DstPackets','SrcBytes','DstBytes'])\n",
    "print('elapsed',round(time.time()-start_time,2),'seconds')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "nfdf.to_pickle(\"netflow_day_02_1E6rows.pkl\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "elapsed 0.8 seconds\n"
     ]
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "nfdf = pandas.read_pickle('netflow_day_02_1E6rows.pkl')\n",
    "print('elapsed',round(time.time()-start_time,2),'seconds')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploration, Characterization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1000000, 11)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfdf.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "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 th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Time</th>\n",
       "      <th>Duration</th>\n",
       "      <th>SrcDevice</th>\n",
       "      <th>DstDevice</th>\n",
       "      <th>Protocol</th>\n",
       "      <th>SrcPort</th>\n",
       "      <th>DstPort</th>\n",
       "      <th>SrcPackets</th>\n",
       "      <th>DstPackets</th>\n",
       "      <th>SrcBytes</th>\n",
       "      <th>DstBytes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>118781</td>\n",
       "      <td>5580</td>\n",
       "      <td>Comp364445</td>\n",
       "      <td>Comp547245</td>\n",
       "      <td>17</td>\n",
       "      <td>Port05507</td>\n",
       "      <td>Port46272</td>\n",
       "      <td>0</td>\n",
       "      <td>755065</td>\n",
       "      <td>0</td>\n",
       "      <td>1042329018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>118783</td>\n",
       "      <td>6976</td>\n",
       "      <td>Comp450942</td>\n",
       "      <td>Comp829338</td>\n",
       "      <td>6</td>\n",
       "      <td>Port03137</td>\n",
       "      <td>445</td>\n",
       "      <td>1665</td>\n",
       "      <td>1108</td>\n",
       "      <td>300810</td>\n",
       "      <td>250408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>118785</td>\n",
       "      <td>14178</td>\n",
       "      <td>IP564116</td>\n",
       "      <td>Comp141988</td>\n",
       "      <td>17</td>\n",
       "      <td>5060</td>\n",
       "      <td>5060</td>\n",
       "      <td>1866</td>\n",
       "      <td>0</td>\n",
       "      <td>1477041</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>118785</td>\n",
       "      <td>28147</td>\n",
       "      <td>IP564116</td>\n",
       "      <td>Comp141988</td>\n",
       "      <td>17</td>\n",
       "      <td>5060</td>\n",
       "      <td>5060</td>\n",
       "      <td>3326</td>\n",
       "      <td>0</td>\n",
       "      <td>2656305</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>118785</td>\n",
       "      <td>48507</td>\n",
       "      <td>IP564116</td>\n",
       "      <td>Comp141988</td>\n",
       "      <td>17</td>\n",
       "      <td>5060</td>\n",
       "      <td>5060</td>\n",
       "      <td>5423</td>\n",
       "      <td>0</td>\n",
       "      <td>4388449</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Time  Duration   SrcDevice   DstDevice  Protocol    SrcPort    DstPort  \\\n",
       "0  118781      5580  Comp364445  Comp547245        17  Port05507  Port46272   \n",
       "1  118783      6976  Comp450942  Comp829338         6  Port03137        445   \n",
       "2  118785     14178    IP564116  Comp141988        17       5060       5060   \n",
       "3  118785     28147    IP564116  Comp141988        17       5060       5060   \n",
       "4  118785     48507    IP564116  Comp141988        17       5060       5060   \n",
       "\n",
       "   SrcPackets  DstPackets  SrcBytes    DstBytes  \n",
       "0           0      755065         0  1042329018  \n",
       "1        1665        1108    300810      250408  \n",
       "2        1866           0   1477041           0  \n",
       "3        3326           0   2656305           0  \n",
       "4        5423           0   4388449           0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nfdf.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# visualize using Networkx\n",
    "\n",
    "Here I provide code to visualize a graph"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://networkx.github.io/documentation/stable/reference/generated/networkx.convert_matrix.from_pandas_edgelist.html#networkx.convert_matrix.from_pandas_edgelist"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    G.clear()\n",
    "except NameError:\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following line allows you to select the number of rows used in the graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "G = nx.from_pandas_edgelist(nfdf[0:10],'SrcDevice','DstDevice','Duration')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "G.number_of_nodes()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### no labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.6/site-packages/networkx/drawing/nx_pylab.py:611: MatplotlibDeprecationWarning: isinstance(..., numbers.Number)\n",
      "  if cb.is_numlike(alpha):\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nx.draw(G, with_labels = False, node_size = 100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oo2rTpo0SEhJMzwEA444cOaLQ0FBNnDhRERERpud4DK8hGxYfH69vvvlGOTk5pqcAgBWuueYaLVy4UL///e9155136rbbbjM9ySO4kA0qKSnRwIEDVVZWprZt25qeAwBWmTFjhmbOnKmSkhI1a9bM9JwGR5ANOXjwoJxOpxITEzVgwADTcwDAOm63W1FRUfrpT3+q5ORk03MaHD8YxIAzZ87o8ccfV0REBDEGgB/hcDiUnJystWvXau7cuabnNDguZAMmTZqkvLw8/f3vf1dQUJDpOQBgtU2bNqlPnz5au3atOnbsaHpOgyHIHrZu3TpFRESooqJCN910k+k5AOAV0tLSFBcXpw0bNugnP/mJ6TkNgiB70P79++V0OpWamqoHH3zQ9BwA8Bput1tPPvmkJGn27NlyOBxmBzUAXkP2kNraWj322GN68skniTEAXCaHw6Hp06eroqJC6enppuc0CC5kD3n99ddVUFCg1atXKzCQv/4NAFdiy5Yt6tWrl9asWaPOnTubnlOvuJA9YM2aNUpKSlJ2djYxBoCr0LFjR8XHx8vlcunYsWOm59QrLuQGtmfPHoWGhmru3Ln63e9+Z3oOAPiE2NhYHTt2TFlZWT7zejIXcgM6ffq0IiMjNXz4cGIMAPUoISFB//rXvzRz5kzTU+oNF3IDGjNmjMrLy5Wfn69GjRqZngMAPuXzzz9Xz549tWLFCjmdTtNzrhoXcgPJz89XRkaG5s6dS4wBoAHcfvvtevfddxUREaHq6mrTc64aF3ID2LVrl7p27aqcnBzdd999pucAgE97+umntWfPHuXm5nr168lcyPWspqZGQ4YM0bPPPkuMAcAD4uLitHPnTk2dOtX0lKvChVzPXnjhBW3ZskV5eXkKCODrHQDwhC+//FLdu3dXXl6eunfvbnrOFaEY9ej9999XTk6O5syZQ4wBwINuueUWJScna8iQITp06JDpOVeEC7me7NixQ927d9fSpUt11113mZ4DAH7pueee07Zt27R06VKvO4y8a62lvv/+e0VERGj06NHEGAAMmjRpkg4cOKC4uDjTUy4bF3I9GDlypHbt2qVFixZ59Xf4AYAv+Oqrr9StWzfl5ubqnnvuMT3nknEhX6Xc3Fx98MEHSk9PJ8YAYIHWrVsrLS1NkZGRqqqqMj3nknEhX4Xt27fr7rvv1vLlyxUWFmZ6DgDg/3nppZf08ccfa/ny5V7xerL9Cy118uRJuVwujRs3jhgDgIXGjx+vEydOaOLEiaanXBIu5Cs0fPhwHT58WPPnz+epagCw1O7duxUWFqasrCz17t3b9JwL4kK+AllZWSooKFBKSgoxBgCLtWrVSnPmzFF0dLT27t1res4FcSFfpq1bt+ree+/V6tWr9Zvf/Mb0HADAJRg3bpyKioq0atUqa3/hDxfyZThx4oRcLpcmTpxIjAHAi7z66qtyOBx67bXXTE/5UVzIl2HYsGE6ffq0MjIyeKoaALzMvn37FBoaqrS0NPXt29f0nB8IND3AW6Snp6u0tFTl5eXEGAC80I033qh58+Zp6NChqqioUKtWrUxPOgcX8iXYvHmzevfurbVr16pjx46m5wAArsKbb76p/Px8FRYWKjDQnruU15Av4vjx4woPD1dcXBwxBgAfMHr0aDVv3lyvvPKK6Snn4EK+ALfbrejoaDVr1kypqamm5wAA6smBAwfkdDo1ffp0Pfzww6bnSOI15AtKSUnR5s2bVVpaanoKAKAeXXfddZo/f74GDRqksrIytWnTxvQkLuQf8/HHH6tv375av369br/9dtNzAAAN4G9/+5tyc3O1bt06NW7c2OgWXkM+j+rqarlcLk2bNo0YA4AP+8tf/qIbbrhBo0aNMj2FIKuyUhoxQgoJkQIC5A4JUanTqaju3TVkyBDT6wAADcjhcCgjI0NLlizRyhkzzumBQkLq/nNlpWe2+PVT1vn5Uni4VFNT93ZWjaTA4GA5cnOlfv3M7QMAeMS/33lHNz/7rJoFBspx+vT//RdBQXVvHuiB/wa5slLq3Fk6ceLHPyY4WNq0SWrXznO7AACeZUkP/Pcp67i4c67i86qpkeLjPbMHAGCGJT3w3ws5JEQ6duzSPq66uuH3AADMsKQH/hvkgADpUv7VAwKk2tqG3wMAMMOSHvjvU9bNm9fvxwEAvJMlPfDfIEdH133n3IUEBUkxMZ7ZAwAww5Ie+O9T1pZ8Vx0AwDBLeuC/F3K7dnV/ryw4+IdfGQUF1b0/N5cYA4Cvs6QH/htkqe4veW/aJMXGnvuTWWJj697PDwUBAP9gQQ/89ylrAAAs4t8XMgAAliDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMgAAFiDIAABYgCADAGABggwAgAUIMsyrrJRGjJBCQqSAgLp/jhhR937AX/A48HsOt9vtNj0Cfiw/XwoPl2pq6t7+Iyio7i03V+rXz9w+wBN4HEAEGSZVVkqdO0snTvz4xwQHS5s2Se3aeW4X4Ek8DnAWT1nDnLi4c6+B86mpkeLjPbMHMIHHAc7iQoY5ISHSsWOX9nHV1Q2/BzCBxwHOIsgwJyBAuoQ/frWSAht+DWBErS7xqcqAAKm2toHXwCQ+z8Gc5s0v6TJoFBIiN5cBfNWlXsjNmzf8FhjFa8gwJzq67jtILyQoSIqJ8cwewAQeBziLp6xhDt9dCvA4wP/iQoY57drV/f3K4OAfXghBQXXvz83lkxB8G48DnEWQYVa/fnVf+cfGnvsTimJj697PD0OAP+BxAPGUNQAAVuBCBgDAAgQZAAALEGQAACxAkAEAsABBBgDAAgQZAAALEGQAACxAkAEAsABBBgDAAgQZAAALEGQAACxAkAEAsABBBgDAAgQZAAALEGQAACxAkAEAsABBBgDAAgQZAAALEGQAACxAkAEAsABBBgDAAgQZAAALEGQAACxAkAEAsABBBgDAAgQZAAALEGQAACxAkAEAsABBBgDAAgQZAAALEGQAACxAkAEAsABBBgDAAv8DVgUNbbGqN78AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nx.draw(G, with_labels=False,node_size=100,pos = nx.circular_layout(G))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pos = nx.spring_layout(G)\n",
    "nx.draw(G,with_labels=True)\n",
    "nx.draw_networkx_edge_labels(G,pos=pos,with_labels=True)\n",
    "_=plt.axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TASK: what number of nodes makes the visualization unreadable?\n",
    "\n",
    "You have a dataframe with 1,000,000 rows. \n",
    "\n",
    "First, design your experiments. What number of rows will you explore to address the question? \n",
    "\n",
    "At what point does node and/or edge labeling provide value?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}