I want code to render n bits with n + x bits, non-sequentially. I'd Google it but my Google-fu isn't working because I don't know the term for it.
For example, the input value in the first column (2 bits) might be encoded as any of the output values in the comma-delimited second column (4 bits) below:
0 1,2,7,9
1 3,8,12,13
2 0,4,6,11
3 5,10,14,15
My goal is to take a list of integer IDs, and transform them in a way they can still be used for persistent URLs, but that can't be iterated/enumerated sequentially, and where a client cannot determine programmatically if a URL in a search result set has been visited previously without visiting it again.
I would term this process "encoding". You'll see something similar done to permit the use of communications channels that have special symbols that are not permitted in data. Examples: uuencoding and base64 encoding.
That said, you still need to (and appear at first blush to have) ensure that there is only one correct de-code; and accept the increase in size of the output (in the case above, the output will be double the size, bit-for-bit as the input).
I think you'd be better off encrypting the number with a cheap cypher + a constant secret key stored on your server(s), adding a random character or four at the end, and a cheap checksum, and simply reject any responses that don't have a valid checksum.
<encrypt(secret)>
<integer>+<random nonsense>
</encrypt>
+
<checksum()>
<integer>+<random nonsense>
</checksum>
Then decrypt the first part (remember, cheap == fast), validate the ciphertext using the checksum, throw off the random nonsense, and use the integer you stored.
There are probably some cryptographic no-no's here, but let's face it, the cost of this algorithm being broken is a touch on the low side.
Related
I have recently been looking into Bitcoin and the proof of work system.
In this system, when mining, a user has a "challenge string" that they need to concatenate with the CORRECT "proof string"(nonce) and hash, the outcome of that hash starts with a prefix of leading zeros and that's how they verify the block.
My question is, when combining that "challenge string" and the CORRECT "proof string"(nonce), why does the corresponding hash of those values start with the prefix of zeros? How does that work?
The combination of "Challenge string" and "proof of string" is sent to a hashing function, which is a one way function and results in a "random string" (The condition on "random string" is that it should have x number of zeroes in the beginning. The difficulty of guessing increases day to day, which is nothing but x increases).
The job of a Miner is to guess the "proof of string" until the condition on the "random string" is met.
So, it is a pure guessing game. GPUs are very good at generating random numbers very quickly. That is why miners around the world are using top class GPUs to mine the bitcoin transactions.
Not specific to Bitcoin but Bitcoin uses the same mechanism, see https://en.wikipedia.org/wiki/Hashcash for a description of how Proof Of Work "works" and why it works that way.
The short answer is that you are creating a hash collision (https://en.wikipedia.org/wiki/Collision_resistance) and the more leading zeros there are the more difficult it is to create the collision.
In Bitcoin, the difficulty is algorithmically chosen based on the compute on the bitcoin network. This typically only goes up, but should the compute go down the dificulty will also go down. The algorithm adjusts dificulty to keep transaction verification time around 10 minutes.
I'm trying to find 2 different plain text words that create very similar hashes.
I'm using the hashing method 'whirlpool', but I don't really need my question to be answered in the case or whirlpool, if you can using md5 or something easier that's ok.
The similarities i'm looking for is that they contain the same number of letters (doesnt matter how much they're jangled up)
i.e
plaintext 'test'
hash 1: abbb5 has 1 a , 3 b's , one 5
plaintext 'blahblah'
hash 2: b5bab must have the same, but doesnt matter what order.
I'm sure I can read up on how they're created and break it down and reverse it, but I am just wondering if what I'm talking about occurs.
I'm wondering because I haven't found a match of what I'm explaining (I created a PoC to run threw random words / letters till it recreated a similar match), but then again It would take forever doing it the way i was dong it. and was wondering if anyone with real knowledge of hashes / encryption would help me out.
So you can do it like this:
create an empty sorted map \
create a 64 bit counter (you don't need more than 2^63 inputs, in all probability, since you would be dead before they would be calculated - unless quantum crypto really takes off)
use the counter as input, probably easiest to encode it in 8 bytes;
use this as input for your hash function;
encode output of hash in hex (use ASCII bytes, for speed);
sort hex on number / alphabetically (same thing really)
check if sorted hex result is a key in the map
if it is, show hex result, the old counter from the map & the current counter (and stop)
if it isn't, put the sorted hex result in the map, with the counter as value
increase counter, goto 3
That's all folks. Results for SHA-1:
011122344667788899999aaaabbbcccddeeeefff for both 320324 and 429678
I don't know why you want to do this for hex, the hashes will be so large that they won't look too much alike. If your alphabet is smaller, your code will run (even) quicker. If you use whole output bytes (i.e. 00 to FF instead of 0 to F) instead of hex, it will take much more time - a quick (non-optimized) test on my machine shows it doesn't finish in minutes and then runs out of memory.
if i have a hash say like this: 0d47aeda9d97686ab3da96bae2c93d078a5ab253
how do i do the math to find out the number of possibilities to try if i start with 0000000000000000000000000000000000000000 to 9999999999999999999999999999999999999999 which is the general length of a sha1.
The number of possibilities would be 2^(X) where X is the number of bits in the hash.
In the normal hexadecimal string representation of the hash value like the one you gave, each character is 4 bits, so it would be 2^(4*len) where len is the string length of the hash value. In your example, you have a 40 character SHA1 digest, which corresponds to 160 bits, or 2^160 == 1.4615016373309029182036848327163e+48 values.
An SHA-1 hash is 160 bits, so there are 2^160 possible hashes.
Your hexadecimal digit range is 0 through f.
Then it's simply 16^40 or however many characters it contains
Recall that a hash function accepts inputs of arbitrary length. A good cryptographic hash function will seem to assign a "random" hash result to any input. So if the digest is N bits long (for SHA-1, N=160), then every input will be hashed to one of 2^N possible results, in a manner we'll treat as random.
That means that the expectation for finding a preimage for your hash result is running though 2^N inputs. They don't have to be specifically the range that you suggested - any 2^N distinct inputs are fine.
This also means that 2^N inputs don't guarantee that you'll find a preimage - each try is random, so you might miss your 1-in-2^N chance in every single one of those 2^N inputs (just like flipping a coin twice doesn't guarantee you'll get heads at least once). But you can figure out how many inputs are required to find a preimage for the hash with probability p or greater - with p being as close to one as you desire (just not actually 1).
maximum variations, with repeating and with attention to the order are defined as n^k. in your case this would mean 10^40, which can't be correct for SHA1. Reading Wikipedia it sais SHA1 has a max. complexity for a collision based attack of 2^80, using different technices researches were allready successfull with 2^51 collisions, so 10^40 seems a bit much.
I have some base-64 encoded encrypted data and noticed a fair amount of repetition. In a (approx) 200-character-long string, a certain base-64 character is repeated up to 7 times in several separate repeated runs.
Is this a red flag that there is a problem in the encryption? According to my understanding, encrypted data should never show significant repetition, even if the plaintext is entirely uniform (i.e. even if I encrypt 2 GB of nothing but the letter A, there should be no significant repetition in the encrypted version).
According to the binomial distribution, there is about a 2.5% chance that you'd see one character from a set of 64 appear seven times in a series of 200 random characters. That's a small chance, but not negligible. With more information, you might raise your confidence from 97.5% to something very close to 100% … or find that the cipher text really is uniformly distributed.
You say that the "character is repeated up to 7 times" in several separate repeated runs. That's not enough information to say whether the cipher text has a bias. Instead, tell us the total number of times the character appeared, and the total number of cipher text characters. For example, "it appeared a total of 3125 times in 1000 runs of 200 characters each."
Also, you need to be sure that you are talking about the raw output of a cipher. Cipher text is often encapsulated in an "envelope" like that defined by the Cryptographic Message Syntax. Of course, this enclosing structure will have predictable patterns.
Well I guess it depends. Repetition in general is bad thing if it represents the same data.
Considering you are encoding it have you looked at data to see if you have something that repeats in those counts?
In order to understand better you gotta know what kind of encryption does it use.
It could be just coincidence that they are repeating.
But if repetition comes from same data, then it can be a red flag because then frequency counts can be used to decode it.
What kind of encryption are you using? Home made or some industry standard?
It depends on how are you encrypting your data.
Base64 encoding a string may count as light obfuscation, but it is NOT encryption. The purpose of Base64 encoding is to allow any sort of binary data to be encoded as a safe ASCII string.
If an encrypted file exists and someone wants to decrypt it, there are several methods do try.
For example, if you would chose a brute force attack, that's easy: just try all possible keys and you will find the correct one. For this question, it doesn't matter that this might take too long.
But trying keys means the following steps:
Chose key
Decrypt data with key
Check if decryption was successful
Besides the problem that you would need to know the algorithm that was used for the encryption, I cannot imagine how one would do #3.
Here is why: After decrypting the data, I get some "other" data. In case of an encrypted plain text file in a language that I can understand, I can now check if the result is a text in that langauge.
If it would be a known file type, I could check for specific file headers.
But since one tries to decrypt something secret, it is most likely unknown what kind of information there will be if correctly decrypted.
How would one check if a decryption result is correct if it is unknown what to look for?
Like you suggest, one would expect the plaintext to be of some know format, e.g., a JPEG image, a PDF file, etc. The idea would be that it is very unlikely that a given ciphertext can be decrypted into both a valid JPEG image and a valid PDF file (but see below).
But it is actually not that important. When one talks about a cryptosystem being secure, one (roughly) talks about the odds of you being able to guess the plaintext corresponding to a given ciphertext. So I pick a random message m and encrypts it c = E(m). I give you c and if you cannot guess m, then we say the cryptosystem is secure, otherwise it's broken.
This is just a simple security definition. There are other definitions that require the system to be able to hide known plaintexts (semantic security): you give me two messages, I encrypt one of them, and you will not be able to tell which message I chose.
The point is, that in these definitions, we are not concerned with the format of the plaintexts, all we require is that you cannot guess the plaintext that was encrypted. So there is no step 3 :-)
By not considering your step 3, we make the question of security as clear as possible: instead of arguing about how hard it is to guess which format you used (zip, gzip, bzip2, ...) we only talk about the odds of breaking the system compared to the odds of guessing the key. It is an old principle that you should concentrate all your security in the key -- it simplifies things dramatically when your only assumption is the secrecy of the key.
Finally, note that some encryption schemes makes it impossible for you to verify if you have the correct key since all keys are legal. The one-time pad is an extreme example such a scheme: you take your plaintext m, choose a perfectly random key k and compute the ciphertext as c = m XOR k. This gives you a completely random ciphertext, it is perfectly secure (the only perfectly secure cryptosystem, btw).
When searching for an encryption key, you cannot know when you've found the right one. This is because c could be an encryption of any file with the same length as m: if you encrypt the message m' with the key *k' = c XOR m' you'll see that you get the same ciphertext again, thus you cannot know if m or m' was the original message.
Instead of thinking of exclusive-or, you can think of the one-time pad like this: I give you the number 42 and tell you that is is the sum of two integers (negative, positive, you don't know). One integer is the message, the other is the key and 42 is the ciphertext. Like above, it makes no sense for you to guess the key -- if you want the message to be 100, you claim the key is -58, if you want the message to be 0, you claim the key is 42, etc. One time pad works exactly like this, but on bit values instead.
About reusing the key in one-time pad: let's say my key is 7 and you see the ciphertexts 10 and 20, corresponding to plaintexts 3 and 13. From the ciphertexts alone, you now know that the difference in plaintexts is 10. If you somehow gain knowledge of one of the plaintext, you can now derive the other! If the numbers correspond to individual letters, you can begin looking at several such differences and try to solve the resulting crossword puzzle (or let a program do it based on frequency analysis of the language in question).
You could use heuristics like the unix
file
command does to check for a known file type. If you have decrypted data that has no recognizable type, decrypting it won't help you anyway, since you can't interpret it, so it's still as good as encrypted.
I wrote a tool a little while ago that checked if a file was possibly encrypted by simply checking the distribution of byte values, since encrypted files should be indistinguishable from random noise. The assumption here then is that an improperly decrypted file retains the random nature, while a properly decrypted file will exhibit structure.
#!/usr/bin/env python
import math
import sys
import os
MAGIC_COEFF=3
def get_random_bytes(filename):
BLOCK_SIZE=1024*1024
BLOCKS=10
f=open(filename)
bytes=list(f.read(BLOCK_SIZE))
if len(bytes) < BLOCK_SIZE:
return bytes
f.seek(0, 2)
file_len = f.tell()
index = BLOCK_SIZE
cnt=0
while index < file_len and cnt < BLOCKS:
f.seek(index)
more_bytes = f.read(BLOCK_SIZE)
bytes.extend(more_bytes)
index+=ord(os.urandom(1))*BLOCK_SIZE
cnt+=1
return bytes
def failed_n_gram(n,bytes):
print "\t%d-gram analysis"%(n)
N = len(bytes)/n
states = 2**(8*n)
print "\tN: %d states: %d"%(N, states)
if N < states:
print "\tinsufficient data"
return False
histo = [0]*states
P = 1.0/states
expected = N/states * 1.0
# I forgot how this was derived, or what it is suppose to be
magic = math.sqrt(N*P*(1-P))*MAGIC_COEFF
print "\texpected: %f magic: %f" %(expected, magic)
idx=0
while idx<len(bytes)-n:
val=0
for x in xrange(n):
val = val << 8
val = val | ord(bytes[idx+x])
histo[val]+=1
idx+=1
count=histo[val]
if count - expected > magic:
print "\tfailed: %s occured %d times" %( hex(val), count)
return True
# need this check because the absence of certain bytes is also
# a sign something is up
for i in xrange(len(histo)):
count = histo[i]
if expected-count > magic:
print "\tfailed: %s occured %d times" %( hex(i), count)
return True
print ""
return False
def main():
for f in sys.argv[1:]:
print f
rand_bytes = get_random_bytes(f)
if failed_n_gram(3,rand_bytes):
continue
if failed_n_gram(2,rand_bytes):
continue
if failed_n_gram(1,rand_bytes):
continue
if __name__ == "__main__":
main()
I find this works reasonable well:
$ entropy.py ~/bin/entropy.py entropy.py.enc entropy.py.zip
/Users/steve/bin/entropy.py
1-gram analysis
N: 1680 states: 256
expected: 6.000000 magic: 10.226918
failed: 0xa occured 17 times
entropy.py.enc
1-gram analysis
N: 1744 states: 256
expected: 6.000000 magic: 10.419895
entropy.py.zip
1-gram analysis
N: 821 states: 256
expected: 3.000000 magic: 7.149270
failed: 0x0 occured 11 times
Here .enc is the source ran through:
openssl enc -aes-256-cbc -in entropy.py -out entropy.py.enc
And .zip is self-explanatory.
A few caveats:
It doesn't check the entire file, just the first KB, then random blocks from the file. So if a file was random data appended with say a jpeg, it will fool the program. The only way to be sure if to check the entire file.
In my experience, the code reliably detects when a file is unencrypted (since nearly all useful data has structure), but due to its statistical nature may sometimes misdiagnose an encrypted/random file.
As it has been pointed out, this kind of analysis will fail for OTP, since you can make it say anything you want.
Use at your own risk, and most certainly not as the only means of checking your results.
One of the ways is compressing the source data with some standard algorithm like zip. If after decryption you can unzip the result - it's decrypted right. Compression is almost usually done by encryption programs prior to encryption - because it's another step the bruteforcer will need to repeat for each trial and lose time on it and because encrypted data is almost surely uncompressible (size doesn't decrease after compression with a chained algorithm).
Without a more clearly defined scenario, I can only point to cryptanalysis methods. I would say it's generally accepted that validating the result is an easy part of cryptanalysis. In comparison to decrypting even a known cypher, a thorough validation check costs little cpu.
are you seriously asking questions like this?
well if it was known whats inside then you would not need to decrypt it anywayz right?
somehow this has nothing to do with programming question its more mathematical. I took some encryption math classes at my university.
And you can not confirm without a lot of data points.
Sure if your result makes sense and its clear it is meaningful in plain english (or whatever language is used) but to answer your question.
If you were able to decrypt you should be able to encrypt as well.
So encrypt the result using reverse process of decryption and if you get same results you might be golden...if not something is possibly wrong.