I'm trying to asses if Kafka could be used to scale-out our current solution.
I can identify partitions easily. Currently, the requirement is there to be 1500 partitions, each having 1-2 events per second, but future might go as high as 10000 partitions.
But there is one part of our solution which I don't know how would be solved in Kafka.
The problem is that each message contains a string and I want to assign a unique ID to each string across the whole topic. So same strings have the same ID while different strings have different IDs. The IDs don't need to be sequential, nor do they need to be always-growing.
The IDs will then be used down-stream as unique keys to identify those strings. The strings can be hundreds of characters long, so I don't think they would make efficient keys.
More advanced usage would be where messages might have different "kinds" of strings, so there would be multiple unique sequences of IDs. And messages will contain only some of those kinds depending on the type of the message.
Another advanced usage would be that the values are not strings, but structures and if two structures are same would be some more elaborate rule, like if PropA is equal, then structures are equal, if not, then structures are equal if PropB is equal.
To illustrate the problem: Each partition is a computer in a network. Each event is action on the computer. Events need to be ordered per-computer so that events that change the state of the computer (eg. user logged in) can affect other types of events, and ordering is critical for that. Eg. the user opened an application, a file is written, a flash drive is inserted, etc.. And I need each application, file, flash drive, or many others to have unique identifiers across all computers. This is then used to calculate statistics down-stream. And sometimes, an event can have multiple of those, eg. operation on a specific file on the specific flash drive.
There is a very nice post about kafka and blockchain. This is collective mind work and I think this could solve your IDs scalability issue. For solution refer to "Blockchain: reasons." part. All credits goes to respective authors.
Idea is simple, yet efficient:
Data is hash based, with link to previous block
Data may be very well same hashes, links to respective blocks of types
Custom block-chain solution means you in control of data encoding/decoding
Each hash chain is self-contained, and essentially may be your process (hdd/ram/cpu/word/app etc.)
Each hash chain may be a message itself
Bonus: statistics and analytics may be very well stored in block-chain, with high support for compression and replication. Consumers are pretty cheap in that context (scalability).
Proc:
Unique identifier issue solved
All records linked and thanks to kafka & blockchain highly ordered
Data extendable
Kafka properties applied
Cons:
Encryption/Decryption is CPU intensive
Growing level of hash calculation complexity
Problem: without problem context it's hard to approximate the limitations that need to be addressed further. However, assuming calculated solution has a finite nature you should have no issues scaling the solution in a regular way.
Bottom line:
Without knowledge of requirements in terms of speed/cost/quality it's hard to give a better, backed answer with working example. CPU cloud extension may be comparably cheap, data storage - depends on time for how long and what amount of data you want to store, replay-ability, etc. It's a good chunk of work. Prototype? Concept in referenced article.
Forgive me if this question is silly, but I'm starting to learn about consistent hashing and after reading Tom White blog post on it here and realizing that most default hash functions are NOT well mixed I had a thought on ensuring that an arbitrary hash function is minimally well-mixed.
My thought is best explained using an example like this:
Bucket 1: 11000110
Bucket 2: 11001110
Bucket 3: 11010110
Bucket 4: 11011110
Under a standard hash ring implementation for consistent caching across these buckets, you would be get terribly performance, and nearly every entry would be lumped into Bucket 1. However, if we use bits 4&5 as the MSBs in each case then these buckets are suddenly excellently mixed, and assigning a new object to a cache becomes trivial and only requires examining 2 bits.
In my mind this concept could very easily be extended when building distributed networks across multiple nodes. In my particular case I would be using this to determine which cache to place a given piece of data into. The increased placement speed isn't a real concern, but ensuring that my caches are well-mixed is and I was considering just choosing a few bits that are optimally mixed for my given caches. Any information later indexed would be indexed on the basis of the same bits.
In my naive mind this is a much simpler solution than introducing virtual nodes or building a better hash function. That said, I can't see any mention of an approach like this and I'm concerned that in my hashing ignorance I'm doing something wrong here and I might be introducing unintended consequences.
Is this approach safe? Should I use it? Has this approach been used before and are there any established algorithms for determining the minimum unique group of bits?
I am designing a storage cloud software on top of a LAMP stack.
Files could have an internal ID, but it would have many advantages to store them not with an incrementing id as filename in the servers filesystems, but using an hash as filename.
Also hashes as identifier in the database would have a lot of advantages if the currently centralized database should be sharded or decentralized or some sort of master-master high availability environment should be set up. But I am not sure about that yet.
Clients can store files under any string (usually some sort of path and filename).
This string is guaranteed to be unique, because on the first level is something like "buckets" that users have go register like in Amazon S3 and Google storage.
My plan is to store files as hash of the client side defined path.
This way the storage server can directly serve the file without needing the database to ask which ID it is because it can calculate the hash and thus the filename on the fly.
But I am afraid of collisions. I currently think about using SHA1 hashes.
I heard that GIT uses hashes also revision identifiers as well.
I know that the chances of collisions are really really low, but possible.
I just cannot judge this. Would you or would you not rely on hash for this purpose?
I could also us some normalization of encoding of the path. Maybe base64 as filename, but i really do not want that because it could get messy and paths could get too long and possibly other complications.
Assuming you have a hash function with "perfect" properties and assuming cryptographic hash functions approach that the theory that applies is the same that applies to birthday attacks . What this says is that given a maximum number of files you can make the collision probability as small as you want by using a larger hash digest size. SHA has 160 bits so for any practical number of files the probability of collision is going to be just about zero. If you look at the table in the link you'll see that a 128 bit hash with 10^10 files has a collision probability of 10^-18 .
As long as the probability is low enough I think the solution is good. Compare with the probability of the planet being hit by an asteroid, undetectable errors in the disk drive, bits flipping in your memory etc. - as long as those probabilities are low enough we don't worry about them because they'll "never" happen. Just take enough margin and make sure this isn't the weakest link.
One thing to be concerned about is the choice of the hash function and it's possible vulnerabilities. Is there any other authentication in place or does the user simply present a path and retrieve a file?
If you think about an attacker trying to brute force the scenario above they would need to request 2^18 files before they can get some other random file stored in the system (again assuming 128 bit hash and 10^10 files, you'll have a lot less files and a longer hash). 2^18 is a pretty big number and the speed you can brute force this is limited by the network and the server. A simple lock the user out after x attempts policy can completely close this hole (which is why many systems implement this sort of policy). Building a secure system is complicated and there will be many points to consider but this sort of scheme can be perfectly secure.
Hope this is useful...
EDIT: another way to think about this is that practically every encryption or authentication system relies on certain events having very low probability for its security. e.g. I can be lucky and guess the prime factor on a 512 bit RSA key but it is so unlikely that the system is considered very secure.
Whilst the probability of a collision might be vanishingly small, imagine serving a highly confidential file from one customer to their competitor just because there happens to be a hash collision.
= end of business
I'd rather use hashing for things that were less critical when collisions DO occur ;-)
If you have a database, store the files under GUIDs - so not an incrementing index, but a proper globally unique identifier. They work nicely when it comes to distributed shards / high availability etc.
Imagine the worst case scenario and assume it will happen the week after you are featured in wired magazine as an amazing startup ... that's a good stress test for the algorithm.
I've been asked to look for a perfect hash/one way function to be able to hash 10^11 numbers.
However as we'll be using a embedded device it wont have the memory to store the relevant buckets so I was wondering if it's possible to have a decent (minimal) perfect hash without them?
The plan is to use the device to hash the number(s) and we use a rainbow table or a file using the hash as the offset.
Cheers
Edit:
I'll try to provide some more info :)
1) 10^11 is actually now 10^10 so that makes it easer.This number is the possible combinations. So we could get a number between 0000000001 and 10000000000 (10^10).
2) The plan is to us it as part of a one way function to make the number secure so we can send it by insecure means.
We will then look up the original number at the other end using a rainbow table.
The problem is that the source the devices generally have 512k-4Meg of memory to use.
3) it must be perfect - we 100% cannot have a collision .
Edit2:
4) We cant use encryption as we've been told it's not really possable on the devices and keymanigment would be a nightmare if we could.
Edit3:
As this is not sensible, Its purely academic question now (I promise)
Okay, since you've clarified what you're trying to do, I rewrote my answer.
To summarize: Use a real encryption algorithm.
First, let me go over why your hashing system is a bad idea.
What is your hashing system, anyway?
As I understand it, your proposed system is something like this:
Your embedded system (which I will call C) is sending some sort of data with a value space of 10^11. This data needs to be kept confidential in transit to some sort of server (which I will call S).
Your proposal is to send the value hash(salt + data) to S. S will then use a rainbow table to reverse this hash and recover the data. salt is a shared value known to both C and S.
This is an encryption algorithm
An encryption algorithm, when you boil it down, is any algorithm that gives you confidentiality. Since your goal is confidentiality, any algorithm that satisfies your goals is an encryption algorithm, including this one.
This is a very poor encryption algorithm
First, there is an unavoidable chance of collision. Moreover, the set of colliding values differs each day.
Second, decryption is extremely CPU- and memory-intensive even for the legitimate server S. Changing the salt is even more expensive.
Third, although your stated goal is avoiding key management, your salt is a key! You haven't solved key management at all; anyone with the salt will be able to crack the message just as well as you can.
Fourth, it's only usable from C to S. Your embedded system C will not have enough computational resources to reverse hashes, and can only send data.
This isn't any faster than a real encryption algorithm on the embedded device
Most secure hashing algorithm are just as computationally expensive as a reasonable block cipher, if not worse. For example, SHA-1 requires doing the following for each 512-bit block:
Allocate 12 32-bit variables.
Allocate 80 32-bit words for the expanded message
64 times: Perform three array lookups, three 32-bit xors, and a rotate operation
80 times: Perform up to five 32-bit binary operations (some combination of xor, and, or, not, and and depending on the round); then a rotate, array lookup, four adds, another rotate, and several memory loads/stores.
Perform five 32-bit twos-complement adds
There is one chunk per 512-bits of the message, plus a possible extra chunk at the end. This is 1136 binary operations per chunk (not counting memory operations), or about 16 operations per byte.
For comparison, the RC4 encryption algorithm requires four operations (three additions, plus an xor on the message) per byte, plus two array reads and two array writes. It also requires only 258 bytes of working memory, vs a peak of 368 bytes for SHA-1.
Key management is fundamental
With any confidentiality system, you must have some sort of secret. If you have no secrets, then anyone else can implement the same decoding algorithm, and your data is exposed to the world.
So, you have two choices as to where to put the secrecy. One option is to make the encipherpent/decipherment algorithms secret. However, if the code (or binaries) for the algorithm is ever leaked, you lose - it's quite hard to replace such an algorithm.
Thus, secrets are generally made easy to replace - this is what we call a key.
Your proposed usage of hash algorithms would require a salt - this is the only secret in the system and is therefore a key. Whether you like it or not, you will have to manage this key carefully. And it's a lot harder to replace if leaked than other keys - you have to spend many CPU-hours generating a new rainbow table every time it's changed!
What should you do?
Use a real encryption algorithm, and spend some time actually thinking about key management. These issues have been solved before.
First, use a real encryption algorithm. AES has been designed for high performance and low RAM requirements. You could also use a stream cipher like RC4 as I mentioned before - the thing to watch out for with RC4, however, is that you must discard the first 4 kilobytes or so of output from the cipher, or you will be vulnerable to the same attacks that plauged WEP.
Second, think about key management. One option is to simply burn a key into each client, and physically go out and replace it if the client is compromised. This is reasonable if you have easy physical access to all of the clients.
Otherwise, if you don't care about man-in-the-middle attacks, you can simply use Diffie-Hellman key exchange to negotiate a shared key between S and C. If you are concerned about MitMs, then you'll need to start looking at ECDSA or something to authenticate the key obtained from the D-H exchange - beware that when you start going down that road, it's easy to get things wrong, however. I would recommend implementing TLS at that point. It's not beyond the capabilities of an embedded system - indeed, there are a number of embedded commercial (and open source) libraries available already. If you don't implement TLS, then at least have a professional cryptographer look over your algorithm before implementing it.
There is obviously no such thing as a "perfect" hash unless you have at least as many hash buckets as inputs; if you don't, then inevitably it will be possible for two of your inputs to share the same hash bucket.
However, it's unlikely you'll be storing all the numbers between 0 and 10^11. So what's the pattern? If there's a pattern, there may be a perfect hash function for your actual data set.
It's really not that important to find a "perfect" hash function anyway, though. Hash tables are very fast. A function with a very low collision rate - and when hashing integers, that means nearly any simple function, like modulus - is fine and you'll get O(1) average performance.
One concept I've always wondered about is the use of cryptographic hash functions and values. I understand that these functions can generate a hash value that is unique and virtually impossible to reverse, but here's what I've always wondered:
If on my server, in PHP I produce:
md5("stackoverflow.com") = "d0cc85b26f2ceb8714b978e07def4f6e"
When you run that same string through an MD5 function, you get the same result on your PHP installation. A process is being used to produce some value, from some starting value.
Doesn't this mean that there is some way to deconstruct what is happening and reverse the hash value?
What is it about these functions that makes the resulting strings impossible to retrace?
The input material can be an infinite length, where the output is always 128 bits long. This means that an infinite number of input strings will generate the same output.
If you pick a random number and divide it by 2 but only write down the remainder, you'll get either a 0 or 1 -- even or odd, respectively. Is it possible to take that 0 or 1 and get the original number?
If hash functions such as MD5 were reversible then it would have been a watershed event in the history of data compression algorithms! Its easy to see that if MD5 were reversible then arbitrary chunks of data of arbitrary size could be represented by a mere 128 bits without any loss of information. Thus you would have been able to reconstruct the original message from a 128 bit number regardless of the size of the original message.
Contrary to what the most upvoted answers here emphasize, the non-injectivity (i.e. that there are several strings hashing to the same value) of a cryptographic hash function caused by the difference between large (potentially infinite) input size and fixed output size is not the important point – actually, we prefer hash functions where those collisions happen as seldom as possible.
Consider this function (in PHP notation, as the question):
function simple_hash($input) {
return bin2hex(substr(str_pad($input, 16), 0, 16));
}
This appends some spaces, if the string is too short, and then takes the first 16 bytes of the string, then encodes it as hexadecimal. It has the same output size as an MD5 hash (32 hexadecimal characters, or 16 bytes if we omit the bin2hex part).
print simple_hash("stackoverflow.com");
This will output:
737461636b6f766572666c6f772e636f6d
This function also has the same non-injectivity property as highlighted by Cody's answer for MD5: We can pass in strings of any size (as long as they fit into our computer), and it will output only 32 hex-digits. Of course it can't be injective.
But in this case, it is trivial to find a string which maps to the same hash (just apply hex2bin on your hash, and you have it). If your original string had the length 16 (as our example), you even will get this original string. Nothing of this kind should be possible for MD5, even if you know the length of the input was quite short (other than by trying all possible inputs until we find one that matches, e.g. a brute-force attack).
The important assumptions for a cryptographic hash function are:
it is hard to find any string producing a given hash (preimage resistance)
it is hard to find any different string producing the same hash as a given string (second preimage resistance)
it is hard to find any pair of strings with the same hash (collision resistance)
Obviously my simple_hash function fulfills neither of these conditions. (Actually, if we restrict the input space to "16-byte strings", then my function becomes injective, and thus is even provable second-preimage resistant and collision resistant.)
There now exist collision attacks against MD5 (e.g. it is possible to produce a pair of strings, even with a given same prefix, which have the same hash, with quite some work, but not impossible much work), so you shouldn't use MD5 for anything critical.
There is not yet a preimage attack, but attacks will get better.
To answer the actual question:
What is it about these functions that makes the
resulting strings impossible to retrace?
What MD5 (and other hash functions build on the Merkle-Damgard construction) effectively do is applying an encryption algorithm with the message as the key and some fixed value as the "plain text", using the resulting ciphertext as the hash. (Before that, the input is padded and split in blocks, each of this blocks is used to encrypt the output of the previous block, XORed with its input to prevent reverse calculations.)
Modern encryption algorithms (including the ones used in hash functions) are made in a way to make it hard to recover the key, even given both plaintext and ciphertext (or even when the adversary chooses one of them).
They do this generally by doing lots of bit-shuffling operations in a way that each output bit is determined by each key bit (several times) and also each input bit. That way you can only easily retrace what happens inside if you know the full key and either input or output.
For MD5-like hash functions and a preimage attack (with a single-block hashed string, to make things easier), you only have input and output of your encryption function, but not the key (this is what you are looking for).
Cody Brocious's answer is the right one. Strictly speaking, you cannot "invert" a hash function because many strings are mapped to the same hash. Notice, however, that either finding one string that gets mapped to a given hash, or finding two strings that get mapped to the same hash (i.e. a collision), would be major breakthroughs for a cryptanalyst. The great difficulty of both these problems is the reason why good hash functions are useful in cryptography.
MD5 does not create a unique hash value; the goal of MD5 is to quickly produce a value that changes significantly based on a minor change to the source.
E.g.,
"hello" -> "1ab53"
"Hello" -> "993LB"
"ZR#!RELSIEKF" -> "1ab53"
(Obviously that's not actual MD5 encryption)
Most hashes (if not all) are also non-unique; rather, they're unique enough, so a collision is highly improbable, but still possible.
A good way to think of a hash algorithm is to think of resizing an image in Photoshop... say you have a image that is 5000x5000 pixels and you then resize it to just 32x32. What you have is still a representation of the original image but it is much much smaller and has effectively "thrown away" certain parts of the image data to make it fit in the smaller size. So if you were to resize that 32x32 image back up to 5000x5000 all you'd get is a blurry mess. However because a 32x32 image is not that large it would be theoretically conceivable that another image could be downsized to produce the exact same pixels!
That's just an analogy but it helps understand what a hash is doing.
A hash collision is much more likely than you would think. Take a look at the birthday paradox to get a greater understanding of why that is.
As the number of possible input files is larger than the number of 128-bit outputs, it's impossible to uniquely assign an MD5 hash to each possible.
Cryptographic hash functions are used for checking data integrity or digital signatures (the hash being signed for efficiency). Changing the original document should therefore mean the original hash doesn't match the altered document.
These criteria are sometimes used:
Preimage resistance: for a given hash function and given hash, it should be difficult to find an input that has the given hash for that function.
Second preimage resistance: for a given hash function and input, it should be difficult to find a second, different, input with the same hash.
Collision resistance: for a given has function, it should be difficult to find two different inputs with the same hash.
These criterial are chosen to make it difficult to find a document that matches a given hash, otherwise it would be possible to forge documents by replacing the original with one that matched by hash. (Even if the replacement is gibberish, the mere replacement of the original may cause disruption.)
Number 3 implies number 2.
As for MD5 in particular, it has been shown to be flawed:
How to break MD5 and other hash functions.
But this is where rainbow tables come into play.
Basically it is just a large amount of values hashed separetely and then the result is saved to disk. Then the reversing bit is "just" to do a lookup in a very large table.
Obviously this is only feasible for a subset of all possible input values but if you know the bounds of the input value it might be possible to compute it.
Chinese scientist have found a way called "chosen-prefix collisions" to make a conflict between two different strings.
Here is an example: http://www.win.tue.nl/hashclash/fastcoll_v1.0.0.5.exe.zip
The source code: http://www.win.tue.nl/hashclash/fastcoll_v1.0.0.5_source.zip
The best way to understand what all the most voted answers meant is to actually try to revert the MD5 algorithm. I remember I tried to revert the MD5crypt algorithm some years ago, not to recover the original message because it is clearly impossible, but just to generate a message that would produce the same hash as the original hash. This, at least theoretically, would provide me a way to login to a Linux device that stored the user:password in the /etc/passwd file using the generated message (password) instead of using the original one. Since both messages would have the same resulting hash, the system would recognize my password (generated from the original hash) as valid. That didn't work at all. After several weeks, if I remember correctly, the use of salt in the initial message killed me. I had to produce not only a valid initial message, but a salted valid initial message, which I was never able to do. But the knowledge that I got from this experiment was nice.
As most have already said MD5 was designed for variable length data streams to be hashed to a fixed length chunk of data, so a single hash is shared by many input data streams.
However if you ever did need to find out the original data from the checksum, for example if you have the hash of a password and need to find out the original password, it's often quicker to just google (or whatever searcher you prefer) the hash for the answer than to brute force it. I have successfully found out a few passwords using this method.
Now a days MD5 hashes or any other hashes for that matter are pre computed for all possible strings and stored for easy access. Though in theory MD5 is not reversible but using such databases you may find out which text resulted in a particular hash value.
For example try the following hash code at http://gdataonline.com/seekhash.php to find out what text i used to compute the hash
aea23489ce3aa9b6406ebb28e0cda430
f(x) = 1 is irreversible. Hash functions aren't irreversible.
This is actually required for them to fulfill their function of determining whether someone possesses an uncorrupted copy of the hashed data. This brings susceptibility to brute force attacks, which are quite powerful these days, particularly against MD5.
There's also confusion here and elsewhere among people who have mathematical knowledge but little cipherbreaking knowledge. Several ciphers simply XOR the data with the keystream, and so you could say that a ciphertext corresponds to all plaintexts of that length because you could have used any keystream.
However, this ignores that a reasonable plaintext produced from the seed password is much, much more likely than another produced by the seed Wsg5Nm^bkI4EgxUOhpAjTmTjO0F!VkWvysS6EEMsIJiTZcvsh#WI$IH$TYqiWvK!%&Ue&nk55ak%BX%9!NnG%32ftud%YkBO$U6o to the extent that anyone claiming that the second was a possibility would be laughed at.
In the same way, if you're trying to decide between the two potential passwords password and Wsg5Nm^bkI4EgxUO, it's not as difficult to do as some mathematicians would have you believe.
By definition, a cryptographic hash function should not be invertible and should have the least collisions possible.
Regarding your question: it is a one way hash. The input (irrespective of length) will generate a fixed size output, which will be padded based on algo (512 bit boundary for MD5). The information is compressed (lost) and practically not possible to generate from reverse transforms.
Additional info on MD5: it is vulnerable to collisions. I have gone through this article recently,
http://www.win.tue.nl/hashclash/Nostradamus/
Open source code for crypto hash implementations (MD5 and SHA) can be found at Mozilla code.
(freebl library).
I like all the various arguments.
It is obvious the real value of hashed values is simply to provide human-unreadable placeholders for strings such as passwords.
It has no specific enhanced security benefit.
Assuming an attacker gained access to a table with hashed passwords, he/she can:
Hash a password of his/her own choice and place the results inside the password table if he/she has writing/edit rights to the table.
Generate hashed values of common passwords and test the existence of similar hashed values in the password table.
In this case weak passwords cannot be protected by the mere fact that they are hashed.