Naive approach to estimate or calculate the visual difference between characters - algorithm

My starting point was to generate random passwords that are visually easy to recognize. I first decided to omit characters that will be probably visually indistinguishable from the set I choose from randomly. Maybe this is a nonsense idea, because random passwords will be copy-pasted most time. I'm also aware that the difference between two given chars depends on the font, but since every-day fonts are designed to be read by humans, there will be some font-independent characteristics.
Some examples of character pairs that have a low distance from each other in most fonts:
O 0
1 l
5 S
Is there an easy way to "calculate" this sort of distances?
What is the name of this computational discipline, that I can be googled?
Edit: I now found that the term is Homoglyph

Related

What algorithms can group characters into words?

I have some text generated by some lousy OCR software.
The output contains mixture of words and space-separated characters, which should have been grouped into words. For example,
Expr e s s i o n Syntax
S u m m a r y o f T e r minology
should have been
Expression Syntax
Summary of Terminology
What algorithms can group characters into words?
If I program in Python, C#, Java, C or C++, what libraries provide the implementation of the algorithms?
Thanks.
Minimal approach:
In your input, remove the space before any single letter words. Mark the final words created as part of this somehow (prefix them with a symbol not in the input, for example).
Get a dictionary of English words, sorted longest to shortest.
For each marked word in your input, find the longest match and break that off as a word. Repeat on the characters left over in the original "word" until there's nothing left over. (In the case where there's no match just leave it alone.)
More sophisticated, overkill approach:
The problem of splitting words without spaces is a real-world problem in languages commonly written without spaces, such as Chinese and Japanese. I'm familiar with Japanese so I'll mainly speak with reference to that.
Typical approaches use a dictionary and a sequence model. The model is trained to learn transition properties between labels - part of speech tagging, combined with the dictionary, is used to figure out the relative likelihood of different potential places to split words. Then the most likely sequence of splits for a whole sentence is solved for using (for example) the Viterbi algorithm.
Creating a system like this is almost certainly overkill if you're just cleaning OCR data, but if you're interested it may be worth looking into.
A sample case where the more sophisticated approach will work and the simple one won't:
input: Playforthefunofit
simple output: Play forth efunofit (forth is longer than for)
sophistiated output: Play for the fun of it (forth efunofit is a low-frequency - that is, unnatural - transition, while for the is not)
You can work around the issue with the simple approach to some extent by adding common short-word sequences to your dictionary as units. For example, add forthe as a dictionary word, and split it in a post processing step.
Hope that helps - good luck!

How to neglect the output of OCR Engine that has no meaning?

Tesseract OCR engine sometimes outputs text that has no meaning, i want to design an algorithm that neglects any text or word that has no meaning, below is some sort of output text that i want to neglect,my simple solution is to count the words in the recognized text that's separated by " " and the text which has too many words will be garbage(Hint: i'm scanning images which at most will contains 40 words) any idea will be helpful,thanks.
wo:>"|axnoA1wvw\
ldflfig
°J!9O‘ !P99W M9N 6 13!-|15!Cl ‘I-/Vl
978 89l9 Z0 3+ 3 'l9.l.
97 999 VLL lLOZ+ 3 9l!q°lN
wo0'|axno/(#|au1e>1e: new;
1=96r2a1ey\1 1uauud0|e/\e(]
|8UJB){ p8UJL|\7'
Divide the output text into words. Divide the words into triples. Count the triple frequencies, and compare to triple frequencies from text of a known-good text corpus (EG all the articles from some mailing list discussing what you intend to OCR, minus the header lines).
When I say "triples", I mean:
whe, hen, i, say, tri, rip, ipl, ple, les, i, mea, ean
...so "i" has a frequency of 2 in this short example, while the others are all frequency 1.
If you do a frequency count of each of these triples for a large document in your intended language, it should become possible to be reasonably accurate in guessing whether a string is in the same language.
Granted, it's heuristic.
I've used a similar approach for detecting English passwords in a password changing program. It worked pretty well, though there's no such thing as a perfect "obvious password rejecter".
Check the words against a dictionary?
Of course, this will have false-positives for things like foreign-phrases or code. The problem in general is intractable (ex. is this code or gibberish? :) ). The only (nearly) perfect method would be to use this as a heuristic to flag certain sections for human review.

Deducing string transformation rules

I have a set of pairs of character strings, e.g.:
abba - aba,
haha - aha,
baa - ba,
exb - esp,
xa - za
The second (right) string in the pair is somewhat similar to the first (left) string.
That is, a character from the first string can be represented by nothing, itself or a character from a small set of characters.
There's no simple rule for this character-to-character mapping, although there are some patterns.
Given several thousands of such string pairs, how do I deduce the transformation rules such that if I apply them to the left strings, I get the right strings?
The solution can be approximate, working correctly for, say, 80-95% of the strings.
Would you recommend to use some kind of a genetic algorithm? If so, how?
If you could align the characters, or rather groups of characters, you could work out tables saying that aa => a, bb => z, and so on. If you had such tables, you could align the characters using http://en.wikipedia.org/wiki/Dynamic_time_warping. One approach is therefore to guess an alignment (e.g. one for one, just as a starting point, or just align the first and last characters of each sequence), work out a translation table from that, use DTW to get a new alignment, work out a revised translation table, and iterate in that way. Perhaps you could wrap this up with enough maths to show that there is some measure of optimality or probability that such passes increase, climbing to a local maximum.
There is probably some way of doing this by modelling a Hidden Markov Model that generates both sequences simultaneously and then deriving rules from that model, but I would not chose this approach unless I was already familiar with HMMs and had software to use as a starting point that I was happy to modify.
You can use text to speech to create sound waves. then compare sound waves with other's and match them with percentages.
This is my theory how Google has such a advanced spell checker.

Phonetically Memorable Password Generation Algorithms

Background
While at the Gym the other day, I was working with my combination lock, and realized something that would be useful to me as a programmer. To wit, my combination is three seperate sets of numbers that either sound alike, or have some other relation that makes them easy to remember. For instance, 5-15-25, 7-17-2, 6-24-5. These examples seem easy to remember.
Question
How would I implement something similar for passwords? Yes, they ought to be hard to crack, but they also should be easy for the end user to remember. Combination Locks do that with a mix of numbers that have similar sounds, and with numbers that have similar properties (7-17-23: All Prime, 17 rolls right off the tongue after 7, and 23 is another prime, and is (out of that set), the 'hard' one to remember).
Criteria
The Password should be easy to remember. Dog!Wolf is easy to remember, but once an attacker knows that your website gives out that combination, it makes it infinitely easier to check.
The words or letters should mostly follow the same sounds (for the most part).
At least 8 letters
Not use !##$%^&*();'{}_+<>?,./ These punctuation marks, while appropriate for 'hard' passwords, do not have an 'easy to remember' sound.
Resources
This question is language-agnostic, but if there's a specific implementation for C#, I'd be glad to hear of it.
Update
A few users have said that 'this is bad password security'. Don't assume that this is for a website. This could just be for me to make an application for myself that generates passwords according to these rules. Here's an example.
The letters
A-C-C-L-I-M-O-P 'flow', and they happen to be two
regular words put together
(Acclimate and Mop). Further,
when a user says these letters, or
says them as a word, it's an actual
word for them. Easy to remember, but
hard to crack (dictionary attack,
obviously).
This question has a two-part goal:
Construct Passwords from letters that sound similar (using alliteration) or
Construct Passwords that mesh common words similarly to produce a third set of letters that is not in a dictionary.
You might want to look at:
The pronouncable password generation algorithm used by apg and explained in FIPS-181
Koremutake
First of all make sure the password is long. Consider using a "pass-phrase" instead of a single "pass-word". Breaking pass-phrases like "Dogs and wolves hate each other." is very hard yet they are quite easy to remember.
Some sites may also give you an advice which may be helpful, like Strong passwords: How to create and use them (linked from Password checker, which is a useful tool on its own).
Also, instead of trying to create easy to remember password, in some cases a much better alternative is to avoid remembering the password at all by using (and educating your users to use) a good password management utility (see What is your favourite password storage tool?) - when doing this, the only part left is to create a hard to crack password, which is easy (any long enough random sentence will do).
I am surprised no one has mentioned the Multics algorithm described at http://www.multicians.org/thvv/gpw.html , which is similar to the FIPS algorithm but based on trigraphs rather than digraphs. It produces output such as
ahmouryleg
thasylecta
tronicatic
terstabble
I have ported the code to python as well: http://pastebin.com/f6a10de7b
You could use Markov Chains to generate words that sounds like English(or any other language you want) but they are not actual words.
The question of easy to remember is really subjective, so I don't think you can write an algorithm like this that will be good for everyone.
And why use short passwords on web sites/computer applications instead of pass phrases? They are easy to remember but hard to crack.
After many years, I have decided to use the first letter of words in a passphrase. It's impossible to crack, versatile for length and restrictions like "you must have a digit", and hard to make errors.
This works by creating a phrase. A crazy fun vivid topic is useful!
"Stack Overflow aliens landed without using rockets or wheels".
Take the first letter, your password is "soalwurow"
You can type this quickly and accurately since you're not remembering letter by letter, you're just speaking a sentence inside your head.
I also like having words alternate from the left and right side of the keyboard, it gives you a fractionally faster typing speed and more pleasing rhythm. Notice in my example, your hands alternate left-right-left-right.
I have a few times used a following algorithm:
Put all lowercase vowels (from a-z) into an array Vowels
Put all lowercase consonants (from a-z) into another array Consonants
Create a third array Pairs of two letters in such a way, that you create all possible pairs of letters between Vowels and Consonants ("ab", "ba", "ac", etc...)
Randomly pick 3-5 elements from Pairs and concatenate them together as string Password
Randomly pick true or false
If true, remove the last letter from Password
If false, don't do anything
Substitute 2-4 randomly chosen characters in Password with its uppercase equivalent
Substitute 2-4 randomly chosen characters in Password with a randomly chosen integer 0-9
Voilá - now you should have a password of length between 5 and 10 characters, with upper and lower case alphanumeric characters. Having vowels and consonants take turns frequently make them semi-pronounceable and thus easier to remember.
FWIW I quite like jumbling word syllables for an easy but essentially random password. Take "Bongo" for example as a random word. Swap the syllables you get "Gobong". Swap the o's for zeros on top (or some other common substitution) and you've got an essentially random character sequence with some trail that helps you remember it.
Now how you pick out syllables programmatically - that's a whole other question!
When you generate a password for the user and send it by email, the first thing you should do when they first login if force them to change their password. Passwords created by the system do not need to be easy to remember because they should only be needed once.
Having easy to remember, hard to guess passwords is a useful concept for your users but is not one that the system should in some manner enforce. Suppose you send a password to your user's gmail account and the user doesn't change the password after logging in. If the password to the gmail account is compromised, then the password to your system is compromised.
So generating easy to remember passwords for your users is not helpful if they have to change the password immediately. And if they aren't changing it immediately, you have other problems.
I prefer giving users a "hard" password, requiring them to change it on the first use, and giving them guidance on how to construct a good, long pass phrase. I would also couple this with reasonable password complexity requirements (8+ characters, upper/lower case mix, and punctuation or digits). My rationale for this is that people are much more likely to remember something that they choose themselves and less likely to write it down somewhere if they can remember it.
A spin on the 'passphrase' idea is to take a phrase and write the first letters of each word in the phrase. E.g.
"A specter is haunting Europe - the specter of communism."
Becomes
asihe-tsoc
If the phrase happens to have punctation, such as !, ?, etc - might as well shove it in there. Same goes for numbers, or just substitute letters, or add relevant numbers to the end. E.g. Karl Marx (who said this quote) died in 1883, so why not 'asihe-tsoc83'?
I'm sure a creative brute-force attack could capitalise on the statistical properties of such a password, but it's still orders of magnitude more secure than a dictionary attack.
Another great approach is just to make up ridiculous words, e.g. 'Barangamop'. After using it a few times you will commit it to memory, but it's hard to brute-force. Append some numbers or punctuation for added security, e.g. '386Barangamop!'
Here's part 2 of your idea prototyped in a shell script. It takes 4, 5 and 6 letter words (roughly 50,000) from the Unix dictionary file on your computer, and concatenate those words on the first character.
#! /bin/bash
RANDOM=$$
WORDSFILE=./simple-words
DICTFILE=/usr/share/dict/words
grep -ve '[^a-z]' ${DICTFILE} | grep -Ee '^.{4,6}$' > ${WORDSFILE}
N_WORDS=$(wc -l < ${WORDSFILE})
for i in $(seq 1 20); do
password=""
while [ ! "${#password}" -ge 8 ] || grep -qe"^${password}$" ${DICTFILE}; do
while [ -z "${password}" ]; do
password="$(sed -ne "$(( (150 * $RANDOM) % $N_WORDS + 1))p" ${WORDSFILE})"
builtfrom="${password}"
done
word="$(sort -R ${WORDSFILE} | grep -m 1 -e "^..*${password:0:1}")"
builtfrom="${word} ${builtfrom}"
password="${word%${password:0:1}*}${password}"
done
echo "${password} (${builtfrom})"
done
Like most password generators, I cheat by outputting them in sets of twenties. This is often defended in terms of "security" (someone looking over your shoulder), but really its just a hack to let the user just pick the friendliest password.
I found the 4-to-6 letter words from the dictionary file still containing obscure words.
A better source for words would be a written document. I copied all the words on this page and pasted them into a text document, and then ran the following set of commands to get the actual english words.
perl -pe 's/[^a-z]+/\n/gi' ./624425.txt | tr A-Z a-z | sort -u > ./words
ispell -l ./words | grep -Fvf - ./words > ./simple-words
Then I used these 500 or so very simple words from this page to generate the following passwords with the shell script -- the script parenthetically shows the words that make up a password.
backgroundied (background died)
soundecrazy (sounding decided crazy)
aboupper (about upper)
commusers (community users)
reprogrammer (replacing programmer)
alliterafter (alliteration after)
actualetter (actual letter)
statisticrhythm (statistical crazy rhythm)
othereplacing (other replacing)
enjumbling (enjoying jumbling)
feedbacombination (feedback combination)
rinstead (right instead)
unbelievabut (unbelievably but)
createdogso (created dogs so)
apphours (applications phrase hours)
chainsoftwas (chains software was)
compupper (computer upper)
withomepage (without homepage)
welcomputer (welcome computer)
choosome (choose some)
Some of the results in there are winners.
The prototype shows it can probably be done, but the intelligence you require about alliteration or syllable information requires a better data source than just words. You'd need pronunciation information. Also, I've shown you probably want a database of good simple words to choose from, and not all words, to better satisfy your memorable-password requirement.
Generating a single password the first time and every time -- something you need for the Web -- will take both a better data source and more sophistication. Using a better programming language than Bash with text files and using a database could get this to work instantaneously. Using a database system you could use the SOUNDEX algorithm, or some such.
Neat idea. Good luck.
I'm completely with rjh. The advantage of just using the starting letters of a pass-phrase is that it looks random, which makes it damn hard to remember if you don't know the phrase behind it, in case Eve looks over your shoulder as you type the password.
OTOH, if she sees you type about 8 characters, among which 's' twice, and then 'o' and 'r' she may guess it correctly the first time.
Forcing the use of at least one digit doesn't really help; you simply know that it will be "pa55word" or "passw0rd".
Song lyrics are an inexhaustible source of pass-phrases.
"But I should have known this right from the start"
becomes "bishktrfts". 10 letters, even only lowercase gives you 10^15 combinations, which is a lot, especially since there's no shortcut for cracking it. (At 1 million combinations a second it takes 30 years to test all 10^15 combinations.)
As an extra (in case Eve knows you're a Police fan), you could swap e.g. the 2nd and 3rd letter, or take the second letter of the third word. Endless possibilities.
System generated passwords are a bad idea for anything other than internal service accounts or temporary resets (etc).
You should always use your own "passphrases" that are easy for you to remember but that are almost impossible to guess or brute force. For example the password for my old university account was.
Here to study again!
That is 20 characters using upper and lower case with punctuation. This is an unbelievably strong password and there is no piece of software that could generate a more secure one that is easier to remember for me.
Take look at the gpw tool. The package is also available in Debian/Ubuntu repositories.
One way to generate passwords that 'sound like' words would be to use a markov chain. An n-degree markov chain is basically a large set of n-tuples that appear in your input corpus, along with their frequency. For example, "aardvark", with a 2nd-degree markov chain, would generate the tuples (a, a, 1), (a, r, 2), (r, d, 1), (d, v, 1), (v, a, 1), (r, k, 1). Optionally, you can also include 'virtual' start-word and end-word tokens.
In order to create a useful markov chain for your purposes, you would feed in a large corpus of english language data - there are many available, including, for example, Project Gutenburg - to generate a set of records as outlined above. For generating natural language words or sentences that at least mostly follow rules of grammar or composition, a 3rd degree markov chain is usually sufficient.
Then, to generate a password, you pick a random 'starting' tuple from the set, weighted by its frequency, and output the first letter. Then, repeatedly select at random (again weighted by frequency) a 'next' tuple - that is, one that starts with the same letters that your current one ends with, and has only one letter different. Using the example above, suppose I start at (a, a, 1), and output 'a'. My only next choice is (a, r, 2), so I output another 'a'. Now, I can choose either (r, d, 1) or (r, k, 1), so I pick one at random based on their frequency of occurrence. Suppose I pick (r, k, 1) - I output 'r'. This process continues until you reach an end-of-word marker, or decide to stop independently (since most markov chains form a cyclic graph, you can potentially never finish generating if you don't apply an artificial length limitation).
At a word level (eg, each element of the tuple is a word), this technique is used by some 'conversation bots' to generate sensible-seeming nonsense sentences. It's also used by spammers to try and evade spam filters. At a letter level, as outlined above, it can be used to generate nonsense words, in this case for passwords.
One drawback: If your input corpus doesn't contain anything other than letters, nor will your output phrases, so they won't pass most 'secure' password requirements. You may want to apply some post-processing to substitute some characters for numbers or symbols.
edit: After answering, I realized that this is in no way phonetically memorable. Leaving the answer anyway b/c I find it interesting. /edit
Old thread, I know... but it's worth a shot.
1) I'd probably build the largest dictionary you can ammass. Arrange them into buckets by part of speech.
2)Then, build a grammar that can make several types of sentences. "Type" of sentence is determined by permutations of parts of speech.
3)Randomly (or as close to random as possible), pick a type of sentence. What is returned is a pattern with placeholders for parts of speech (n-v-n would be noun-verb-noun)
3)Pick words at random in each part of speech bucket to stand in for the placeholders. Fill them in. (The example above might become something like car-ate-bicycle.)
4)randomly scan each character deciding whether or not you want to replace it with either a similar-sounding character (or set of characters), or a look-alike. This is the hardest step of the problem.
5) resultant password would be something like kaR#tebyCICle
6) laugh at humorous results like the above that look like "karate bicycle"
I would really love to see someone implement passwords with control characters like "<Ctrl>+N" or even combo characters like "A+C" at the same time. Converting this to some binary equivalent would, IMHO, make password requirements much easier to remember, faster to type, and harder to crack (MANY more combinations to check).

How to find "equivalent" texts?

I want to find (not generate) 2 text strings such that, after removing all non letters and ucasing, one string can be translated to the other by simple substitution.
The motivation for this comes from a project I known of that is testing methods for attacking cyphers via probability distributions. I'd like to find a large, coherent plain text that, once encrypted with a simple substitution cypher, can be decrypted to something else that is also coherent.
This ends up as 2 parts, find the longest such strings in a corpus, and get that corpus.
The first part seems to me to be amiable to some sort of attack with a B-tree keyed off the string after a substitution that makes the sequence of first occurrences sequential.
HELLOWORLDTHISISIT
1233454637819a9b98
A little optimization based on knowing the maximum value and length of the string based on each depth of the tree and the rest is just coding.
The Other part would be quite a bit more involved; how to generate a large corpus of text to search? some kind of internet spider would seem to be the ideal approach as it would have access to the largest amount of text but how to strip it to just the text?
The question is; Any ideas on how to do this better?
Edit: the cipher that was being used is an insanely basic 26 letter substitution cipher.
p.s. this is more a thought experiment then a probable real project for me.
There are 26! different substitution ciphers. That works out to a bit over 88 bits of choice:
>>> math.log(factorial(26), 2)
88.381953327016262
The entropy of English text is something like 2 bits per character at least. So it seems to me you can't reasonably expect to find passages of more than 45-50 characters that are accidentally equivalent under substitution.
For the large corpus, there's the Gutenberg Project and Wikipedia, for a start. You can download an dump of all the English Wikipedia's XML files from their website.
I think you're asking a bit much to generate a substitution that is also "coherent". That is an AI problem for the encryption algorithm to figure out what text is coherent. Also, the longer your text is the more complicated it will be to create a "coherent" result... quickly approaching a point where you need a "key" as long as the text you are encrypting. Thus defeating the purpose of encrypting it at all.

Resources