-Plotting with Matplotlib
-------------------------
-
-Also creating a presentation with rst2pdf
-=========================================
-
-Data Structures
----------------
-Favour simpler data structures if they do what you need. In order:
-
-#. Built-in Lists
- - 2xN data or simpler
- - Can't install system dependencies
-#. Numpy arrays
- - 2 (or higher) dimensional data
- - Lots of numerical calculations
-#. Pandas series/dataframes
- - 'Data Wrangling', reshaping, merging, sorting, querying
- - Importing from complex formats
-
-Shamelessly stolen from https://stackoverflow.com/a/45288000
-
-Loading Data from Disk
-----------------------
-Natively
-========
-
-.. code-block:: python
-
- >>> import csv
- >>> with open('eggs.csv', newline='') as csvfile:
- ... spam = csv.reader(csvfile,
- ... delimiter=' ',
- ... quotechar='|')
- ... for row in spam:
- ... # Do things
- ... pass
-
-Loading Data from Disk
-----------------------
-Numpy
-=====
-
-.. code-block:: python
-
- >>> import numpy
- >>> spam = numpy.genfromtxt('eggs.csv',
- ... delimiter=' ',
- ... dtype=None) # No error handling!
- >>> for row in spam:
- ... # Do things
- ... pass
-
-``numpy.genfromtxt`` will try to infer the datatype of each column if
-``dtype=None`` is set.
-
-``numpy.loadtxt`` is generally faster at runtime if your data is well formated
-(no missing values, only numerical data or constant length strings)
-
-Loading Data from Disk
-----------------------
-Numpy NB.
-=========
-**Remind me to look at some actual numpy usage at the end**
-
-- I think numpy does some type coercion when creating arrays.
-- Arrays created by ``numpy.genfromtxt`` can not in general be indexed like
- ``data[xstart:xend, ystart:yend]``.
-- Data of unequal types are problematic! Pandas *may* be a better choice in
- that case.
-- Specifying some value for ``dtype`` is probably necessary in most cases in
- practice: https://docs.scipy.org/doc/numpy/reference/arrays.dtypes.html
-
-Loading Data from Disk
-----------------------
-Pandas
-======
-
-.. code-block:: python
-
- >>> import pandas
- >>> # dtype=None is def
- >>> spam = pandas.read_csv('eggs.csv',
- ... delimiter=' ',
- ... header=None)
- >>> for row in spam:
- ... # Do things
- ... pass
-
-``header=None`` is required if the flie does not have a header.
-
-
-
-Generating Data for Testing
----------------------------
-
-Generating the data on the fly with numpy is convenient.
-
-.. code-block:: python
-
- >>> import numpy.random as ran
- >>> # For repeatability
- >>> ran.seed(7890234)
- >>> # Uniform [0, 1) floats
- >>> data = ran.rand(100, 2)
- >>> # Uniform [0, 1) floats
- >>> data = ran.rand(100, 100, 100)
- >>> # Std. normal floats
- >>> data = ran.randn(100)
- >>> # 3x14x15 array of binomial ints with n = 100, p = 0.1
- >>> data = ran.binomial(100, 0.1, (3, 14, 15))
-
-Plotting Time Series
---------------------
-
-Plot data of the form:
-
-.. math:: y=f(t)
-
-
-Subplots
---------
-
-
-Saving Plots
-------------
-
-So far I've just displayed plots with ``plt.show()``. You can actually save
-the plots from that interface manually, but when scripting, it's convenient
-to do so automatically:
-
-.. code-block:: python
-
- >>> # Some plotting has previously occured
- >>> plt.savefig('eggs.pdf', dpi=300, transparent=False)
-
-The output format is interpreted from the file extension.
-The keyword arguments are optional here. Other options exist.
-
-Error Bars
-----------
-
-
-Stacked Bar Graph
------------------
-
-
-Resources
----------
-NumPy User Guide: https://docs.scipy.org/doc/numpy/user/index.html
-
-NumPy Reference: https://docs.scipy.org/doc/numpy/reference/index.html#reference
-
-Matplotlib example gallery: https://matplotlib.org/gallery/index.html
-
-Pandas: It probably exists. Good luck.
-
-This presentation: https://git.friedersdorff.com/max/plotting_with_matplotlib.git
+Why is Password Reuse a Problem?
+--------------------------------
+.. image:: password_reuse_1.png
+.. image:: password_reuse_2.png
+.. image:: password_reuse_3.png
+
+About password strength
+-----------------------
+How is strength measured?
+=========================
+'Entropy' `s` depends on the size of the alphabet `a` and the length `n` of the
+password:
+
+.. math::
+ s = log_2(a^n)
+
+* 0889234877724602 -> 53 bits
+* ZeZJieatdH -> 60 bits
+
+Why are weak passwords problematic?
+===================================
+Weak passwords are trivial to crack in many situations. A password with 53 bits
+may be cracked by a criminal organisation in less than an hour.
+
+
+What about strong passwords?
+============================
+They are difficult to remember, a problem especially when you use a different
+strong password for every service. You are also tempted to write them down, or
+reuse them.
+
+It's surprisingly difficult for humans to generate good passwords!
+
+Password Managers to the Rescue!
+--------------------------------
+Password managers allow you to create a unique and strong password for every
+service.
+
+Additional benefits:
+
+* Remembers passwords for you
+* Generates passwords for you
+* Automagically fills in passwords on websites for you, this is important!
+* Makes passwords available on all your configured devices
+* Can store additional related data, usernames, answers to security questions,
+ pins for debit/credit cards
+
+Any of the mainstream password manager is equivalent in the above respects.
+
+Can you trust password managers?
+--------------------------------
+Yes*
+
+How do they keep passwords secure?
+----------------------------------
+1. User supplies a password
+2. The password is used to derive an encryption key. This process is designed
+ to be slow, even on modern hardware
+3. The so generated encryption key is used to encrypt/decrypt your passwords
+
+Note that the security of the encryption depends on the strengh of your
+password. With a poor password (50 bits), it would take the entire computing
+power of the world less than a month to crack the database. With a decent ish
+password (60 bits), it would take on the order of 50 years on average. With a
+better password (70 bits), it would take on the order of 50,000 years.
+
+Generating a Strong Password
+----------------------------
+Passphrases are better than passwords:
+
+* Tr0ub4dor&3 -> 28 bits of entropy, hard to remember
+* correct horse battery stable -> 44 bits of entropy, easy to remember
+
+Use passphrases everywhere you have to remember.
+
+Generate passphrases with Diceware
+==================================
+1. Roll 5, 6 sided, *physical* dice
+2. Read the numbers left to right
+3. Find the word with that number on a list 6^5 (7776) words
+4. Repeat until desired length is reached. For a password manager, use at
+ least 7.
+5. Write down your passphrase on paper and keep it somewhere secure
+6. If you are 100% confident that you will not forget the passphrase, destroy
+ the paper by burning
projects / max / intro_dice_and_pmgmnt.git / commitdiff
