173 lines
4.6 KiB
Plaintext
173 lines
4.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"source": [
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"# What does is take to compromise a users nKode in the worst case scenario?\n"
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],
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"metadata": {
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"collapsed": false
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}
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"outputs": [],
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"source": [
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"def compute_time_to_crack_hash(\n",
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" num_of_attributes: int,\n",
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" nkode_len,\n",
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" secs_per_hash: float = 0.5,\n",
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") -> list[float, float]:\n",
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" secs_to_days = 1/(60*60*24)\n",
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" secs_to_years = secs_to_days / 365\n",
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" total_secs_to_compute_half_of_hashes = num_of_attributes ** nkode_len * secs_per_hash * 0.5\n",
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" return [round(total_secs_to_compute_half_of_hashes * secs_to_days, 2), round(total_secs_to_compute_half_of_hashes * secs_to_years, 2)]\n"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-07-26T15:29:35.667921Z",
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"start_time": "2024-07-26T15:29:35.664278Z"
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}
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}
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},
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{
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"cell_type": "code",
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"execution_count": 21,
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"outputs": [],
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"source": [
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"def matrix_to_md_table(col_names: list[str], mat: list[list[any]]) -> str:\n",
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" assert len(col_names) == len(mat[0])\n",
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" numb_cols = len(col_names)\n",
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" table = \"|\" + \"|\".join(col_names) + \"|\\n\"\n",
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" table += \"|\" + \"|\".join(['-' for _ in range(numb_cols)]) + \"|\\n\"\n",
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" for row in mat:\n",
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" table += \"|\" + \"|\".join([str(el) for el in row]) + \"|\\n\"\n",
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" return table"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-07-27T18:42:04.980503Z",
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"start_time": "2024-07-27T18:42:04.976703Z"
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}
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}
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"|number of attributes|nkode length|days to crack|years to crack|\n",
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"|-|-|-|-|\n",
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"|9|4|0.02|0.0|\n",
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"|9|5|0.17|0.0|\n",
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"|9|6|1.54|0.0|\n",
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"|9|7|13.84|0.04|\n",
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"|9|8|124.56|0.34|\n",
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"|9|9|1121.01|3.07|\n",
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"|9|10|10089.08|27.64|\n",
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"|10|4|0.03|0.0|\n",
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"|10|5|0.29|0.0|\n",
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"|10|6|2.89|0.01|\n",
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"|10|7|28.94|0.08|\n",
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"|10|8|289.35|0.79|\n",
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"|10|9|2893.52|7.93|\n",
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"|10|10|28935.19|79.27|\n",
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"|11|4|0.04|0.0|\n",
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"|11|5|0.47|0.0|\n",
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"|11|6|5.13|0.01|\n",
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"|11|7|56.39|0.15|\n",
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"|11|8|620.25|1.7|\n",
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"|11|9|6822.77|18.69|\n",
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"|11|10|75050.42|205.62|\n",
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"|12|4|0.06|0.0|\n",
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"|12|5|0.72|0.0|\n",
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"|12|6|8.64|0.02|\n",
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"|12|7|103.68|0.28|\n",
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"|12|8|1244.16|3.41|\n",
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"|12|9|14929.92|40.9|\n",
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"|12|10|179159.04|490.85|\n",
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"|13|4|0.08|0.0|\n",
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"|13|5|1.07|0.0|\n",
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"|13|6|13.97|0.04|\n",
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"|13|7|181.56|0.5|\n",
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"|13|8|2360.33|6.47|\n",
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"|13|9|30684.32|84.07|\n",
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"|13|10|398896.1|1092.87|\n",
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"|14|4|0.11|0.0|\n",
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"|14|5|1.56|0.0|\n",
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"|14|6|21.79|0.06|\n",
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"|14|7|305.02|0.84|\n",
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"|14|8|4270.22|11.7|\n",
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"|14|9|59783.12|163.79|\n",
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"|14|10|836963.7|2293.05|\n",
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"|15|4|0.15|0.0|\n",
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"|15|5|2.2|0.01|\n",
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"|15|6|32.96|0.09|\n",
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"|15|7|494.38|1.35|\n",
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"|15|8|7415.77|20.32|\n",
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"|15|9|111236.57|304.76|\n",
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"|15|10|1668548.58|4571.37|\n",
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"\n"
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]
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}
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],
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"source": [
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"time_to_crack = []\n",
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"for num_attr in range(9, 16):\n",
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" for nkod_len in range(4, 11):\n",
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" hash_crack = [num_attr, nkod_len]\n",
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" hash_crack.extend(compute_time_to_crack_hash(num_attr, nkod_len))\n",
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" time_to_crack.append(hash_crack)\n",
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"\n",
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"hash_crack_md = matrix_to_md_table([\"number of attributes\", \"nkode length\", \"days to crack\", \"years to crack\"], time_to_crack)\n",
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"\n",
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"\n",
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"print(hash_crack_md)"
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],
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"metadata": {
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"collapsed": false,
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"ExecuteTime": {
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"end_time": "2024-07-27T18:43:31.002026Z",
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"start_time": "2024-07-27T18:43:30.997876Z"
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}
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}
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"outputs": [],
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"source": "",
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"metadata": {
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"collapsed": false
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}
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 0
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}
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