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So I completely understand the mathematical unlikeliness of creating two GUID values with the same number. But is it acceptable practice to assume they are unique?
For example I am working with a system for dealing with medical files. When I began to layout the database structure the manager (Not very technically knowledgeable, but likes to think he is and delegates things that would be better left for the more technically minded to decide) says he wants to use GUID's to separate different medical records instead of INT because it is "More unique". I explained how an INT is always going to be unique because it is sequential. I suggested we use BigINT if it will make him feel more comfortable since there are more numbers in that then if the population of the planet increased to the point people would only fit standing next to one another across the planet, but he is insisting on using GUIDs.
My feeling is although it is NEARLY IMPOSSIBLE for there to be a mix up, when dealing with medical records, why take the chance? What is the advantage of using a GUID vs an INT in this scenario?
But is it acceptable practice to assume it is unique?
Yes. That is the entire purpose of UUID, to be used as a reliable unique identifier without centralized coordination. (A GUID is Microsoft’s variation of a UUID.)
Only you (or your appropriate management) can make the final judgement for your particular project.
But if you truly begin to appreciate the enormity of the numerical range of 12x bits (which is actually incomprehensible to the human mind), then you know you can remove the usage of a properly generated UUID from your list of worries.
By “properly generated” I mean things like using the date-time Versions, or for lower number of values use the random (Version 4) if backed by a cryptographically-strong random number generator. Nearly every modern operating system today includes a UUID generation library. Or you can use the OSSP UUID project. Improperly-generated would include roll-your-own implementations you may see bandied about the inter webs.
As for the suggestion to use a database’s auto-incrementing serial/sequence number, every database person I know with years of real-world experience has been burned by those. I’ve never heard of or read of anyone ever having a collision with properly-generated UUIDs. I'm not saying sequences are necessarily bad or don't have their place, I'm just saying that all I can do is laugh when I hear people turn away from a UUID because of some beyond-astrononomically incomprehensibly minute possibility of a UUID collision and choose a sequence instead.
when dealing with medical records, why take the chance?
Your medical system is far far more likely to fail because of faulty data-entry or other human error with handling records. But do you post 3 clerks on duty to independently triple-enter the same data to reduce that chance of error? No. And that risk is incomprehensibly mathematically more likely to happen than a UUID problem. Yet every medical facility I know of accepts that enormous risk without even thinking about it.
What is the advantage of using a GUID vs an INT
The advantages include:
No need to manage your sequences.Examples include: Resetting for development, test, and production environments. Or when restoring a backup. Or fixing the sequence after faults in the system’s serial generation library (my own experience).
Avoid users’ intuited assumptions being confused about missing numbers in the sequence. I've had that conversation far too often.
Federating data between distributed systems.This is the biggest advantage, each system can act independently yet easily share data back and forth with other systems. Without UUIDs, the administrative overhead and the risk of error are bothersome at first and only grow over time.
Downsides include:
Larger memory and storage usage.Serial numbers are usually 32-bit integers, sometimes 64-bit. A good database with native support for UUID as a data type will use 128 bits.
Less readable by humans.One workaround is to just read several of the first or last digits for casual work.
Possibly less efficient indexing, with very large number of entries.
using an incrementing integer ID ensures only uniqueness within its own domain/type, an advantage of UUIDs/GUIDs is that they uniquely identify the owning thing in the entire universe.
So if you have multiple objects, say MedicalRecord, ID = 5, VaccinationForm, ID = 5 then you need to specify both the type ("medicalRecord" or "vaccinationForm" with the ID value of 5) whereas with a GUID you only need to store a single quanta of information to uniquely identify it.
It can be argued that using GUIDs is a waste of space as they are 16 bytes long (a 128-bit value).
If your system is self-contained and not interfacing with others you might want to use SQL Server's "sequence" concept, where instead of each table storing its own identity sequence, the sequence is maintained for all tables, making it a Locally-Unique ID value. You can use any size integer too.
See here: https://msdn.microsoft.com/en-us/library/ff878091.aspx
I have a system that needs to schedule some stuff and return identifiers to the scheduled tasks to some foreign objects. The user would basically do this:
identifier = MyLib.Schedule(something)
# Nah, let's unschedule it.
MyLib.Unschedule(identifier)
I use this kind of pattern a lot in internal code, and I always use plain integers as the identifier. But if the identifiers are used by untrusted code, a malicious user could break the entire system by doing a single Unschedule(randint()).
I need the users of the code to be able to only unschedule identifiers they have actually scheduled.
The only solution I can think of is to generate i.e 64-bit random numbers as identifiers, and keep track of which identifiers are currently handed out to avoid the ridiculously unlikely duplicates. Or 128-bit? When can I say "this is random enough, no duplicates could possibly occur", if ever?
Or better yet, is there a more sensible way to do this? Is there a way to generate identifier tokens that the generator can easily keep track of (avoiding duplicates) but is indistinguishable from random numbers to the recipient?
EDIT - Solution based on the accepted answer:
from Crypto.Cipher import AES
import struct, os, itertools
class AES_UniqueIdentifier(object):
def __init__(self):
self.salt = os.urandom(8)
self.count = itertools.count(0)
self.cipher = AES.new(os.urandom(16), AES.MODE_ECB)
def Generate(self):
return self.cipher.encrypt(self.salt +
struct.pack("Q", next(self.count)))
def Verify(self, identifier):
"Return true if identifier was generated by this object."
return self.cipher.decrypt(identifier)[0:8] == self.salt
Depending on how many active IDs you have, 64 bits can be too little. By the birthday paradox, you'd end up with essentially the level of protection you might expect from 32 bit identifiers.
Besides, probably the best way to create these is to use some salted hash function, such as SHA-1 or MD5 or whatever your framework already has, with a randomly chosen salt (kept secret), and those generate at least 128 bits anyway, exactly for the reason mentioned above. If you use something that creates longer hash values, I don't really see any reason to truncate them.
To create identifiers you can check without storing them, take something easy to detect, such as having the same 64 bit patterns twice (giving a total of 128 bits) and encrypt that with some constant secret key, using AES or some other cipher with a block size of 128 bits (or whatever you picked). If and when the user sends some alleged key, decrypt and check for your easy-to-spot pattern.
It sounds to me like you might be over thinking this problem. This sounds 100% like an application for a GUID/UUID. Python even has a built in way to generate them. The whole point of GUID/UUIDs is that the odds of collision are astronomical, and by using a string instead of an encrypted token you can skip the decrypting operation in the verify step. I think this would also eliminate a whole slew of problems you might encounter regarding key management, and increase the speed of the whole process.
EDIT:
With a UUID, your verify method would just be a comparison between the given UUID and the stored one. Since the odds of a collision between two UUIDs is incredibly low, you shouldn't have to worry about false positives. In your example, it appears that the same object is doing both encryption and decryption, without a third party reading the stored data. If this is the case, you aren't gaining anything by passing around encrypted data except that the bits your passing around aren't easy to guess. I think a UUID would give you the same benefits, without the overhead of the encryption operations.
You make your identifier long enough, so it can't be reasonable guessed. In addition, let Unschedule wait for 1 second, if the token is not in use, so a brute force attack is not feasible anymore. Like the other answer said, session IDs in Webapplications are exactly the same problem, and I already saw session IDs which where 64 random characters long.
This is the same problem as dealing with session identifiers in ordinary web applications. Predictable session ids can easily lead to session hijacking.
Have a look at how session ids are generated. Here the content of a typical PHPSESSID cookie:
bf597801be237aa8531058dab94a08a9
If you want to be dead sure no brute-force attack is feasible, do the calculations backward: How many attempts can a cracker do per second? How many different unique id's are used at a random point in time? How many id's are there in total? How long would it take for the cracker to cover, say 1 % of the total space of ids? Adjust number of bits accordingly.
Do you need this pattern in a distributed or local environment?
If you're local, most OO languages should support the notion of object identity, so if you create an opaque handle - just create a new object.
handle = new Object(); // in Java
No other client can fake this.
If you need to use this in distributes environments, you may keep a pool of handles per session, so that a foreign session can never use a stolen handle.
I need to generate unique, incremental, numeric transaction id's for each request I make to a certain XML RPC. These numbers only need to be unique across my domain, but will be generated on multiple machines.
I really don't want to have to keep track of this number in a database and deal with row locking etc on every single transaction. I tried to hack this using a microsecond timestamp, but there were collisions with just a few threads - my application needs to support hundreds of threads.
Any ideas would be appreciated.
Edit: What if each transaction id just has to be larger than the previous request's?
If you're going to be using this from hundreds of threads, working on multiple machines, and require an incremental ID, you're going to need some centralized place to store and lock the last generated ID number. This doesn't necessarily have to be in a database, but that would be the most common option. A central server that did nothing but serve IDs could provide the same functionality, but that probably defeats the purpose of distributing this.
If they need to be incremental, any form of timestamp won't be guaranteed unique.
If you don't need them to be incremental, a GUID would work. Potentially doing some type of merge of the timestamp + a hardware ID on each system could give unique identifiers, but the ID number portion would not necessarily be unique.
Could you use a pair of Hardware IDs + incremental timestamps? This would make each specific machine's IDs incremental, but not necessarily be unique across the entire domain.
---- EDIT -----
I don't think using any form of timestamp is going to work for you, for 2 reasons.
First, you'll never be able to guarantee that 2 threads on different machines won't try to schedule at exactly the same time, no matter what resolution of timer you use. At a high enough resolution, it would be unlikely, but not guaranteed.
Second, to make this work, even if you could resolve the collision issue above, you'd have to get every system to have exactly the same clock with microsecond accuracy, which isn't really practical.
This is a very difficult problem, particularly if you don't want to create a performance bottleneck. You say that the IDs need to be 'incremental' and 'numeric' -- is that a concrete business constraint, or one that exists for some other purpose?
If these aren't necessary you can use UUIDs, which most common platforms have libraries for. They allow you to generate many (millions!) of IDs in very short timespans and be quite comfortable with no collisions. The relevant article on wikipedia claims:
In other words, only after generating
1 billion UUIDs every second for the
next 100 years, the probability of
creating just one duplicate would be
about 50%.
If you remove 'incremental' from your requirements, you could use a GUID.
I don't see how you can implement incremental across multiple processes without some sort of common data.
If you target a Windows platform, did you try Interlocked API ?
Google for GUID generators for whatever language you are looking for, and then convert that to a number if you really need it to be numeric. It isn't incremental though.
Or have each thread "reserve" a thousand (or million, or billion) transaction IDs and hand them out one at a time, and "reserve" the next bunch when it runs out. Still not really incremental.
I'm with the GUID crowd, but if that's not possible, could you consider using db4o or SQL Lite over a heavy-weight database?
If each client can keep track of its own "next id", then you could talk to a sentral server and get a range of id's, perhaps a 1000 at a time. Once a client runs out of id's, it will have to talk to the server again.
This would make your system have a central source of id's, and still avoid having to talk to the database for every id.
I'm using sequential ids as primary keys and there are cases where I don't want those ids to be visible to users, for example I might want to avoid urls like ?invoice_id=1234 that allow users to guess how many invoices the system as a whole is issuing.
I could add a database field with a GUID or something conjured up from hash functions, random strings and/or numeric base conversions, but schemes of that kind have three issues that I find annoying:
Having to allocate the extra database field. I know I could use the GUID as my primary key, but my auto-increment integer PK's are the right thing for most purposes, and I don't want to change that.
Having to think about the possibility of hash/GUID collisions. I give my full assent to all the arguments about GUID collisions being as likely as spontaneous combustion or whatever, but disregarding exceptional cases because they're exceptional goes against everything else I've been taught, and it continues to bother me even when I know I should be more bothered about other things.
I don't know how to safely trim hash-based identifiers, so even if my private ids are 16 or 32 bits, I'm stuck with 128 bit generated identifiers that are a nuisance in urls.
I'm interested in 1-1 mappings of an id range, stretchable or shrinkable so that for example 16-bit ids are mapped to 16 bit ids, 32 bit ids mapped to 32 bit ids, etc, and that would stop somebody from trying to guess the total number of ids allocated or the rate of id allocation over a period.
For example, if my user ids are 16 bit integers (0..65535), then an example of a transformation that somewhat obfuscates the id allocation is the function f(x) = (x mult 1001) mod 65536. The internal id sequence of 1, 2, 3 becomes the public id sequence of 1001, 2002, 3003. With a further layer of obfuscation from base conversion, for example to base 36, the sequence becomes 'rt', '1jm', '2bf'. When the system gets a request to the url ?userid=2bf, it converts from base 36 to get 3003 and it applies the inverse transformation g(x) = (x mult 1113) mod 65536 to get back to the internal id=3.
A scheme of that kind is enough to stop casual observation by casual users, but it's easily solvable by someone who's interested enough to try to puzzle it through. Can anyone suggest something that's a bit stronger, but is easily implementable in say PHP without special libraries? This is getting close to a roll-your-own encryption scheme, so maybe there is a proper encryption algorithm that's widely available and has the stretchability property mentioned above?
EDIT: Stepping back a little bit, some discussion at codinghorror about choosing from three kinds of keys - surrogate (guid-based), surrogate (integer-based), natural. In those terms, I'm trying to hide an integer surrogate key from users but I'm looking for something shrinkable that makes urls that aren't too long, which I don't know how to do with the standard 128-bit GUID. Sometimes, as commenter Princess suggests below, the issue can be sidestepped with a natural key.
EDIT 2/SUMMARY:
Given the constraints of the question I asked (stretchability, reversibility, ease of implementation), the most suitable solution so far seems to be the XOR-based obfuscation suggested by Someone and Breton.
It would be irresponsible of me to assume that I can achieve anything more than obfuscation/security by obscurity. The knowledge that it's an integer sequence is probably a crib that any competent attacker would be able to take advantage of.
I've given some more thought to the idea of the extra database field. One advantage of the extra field is that it makes it a lot more straightforward for future programmers who are trying to familiarise themselves with the system by looking at the database. Otherwise they'd have to dig through the source code (or documentation, ahem) to work out how a request to a given url is resolved to a given record in the database.
If I allow the extra database field, then some of the other assumptions in the question become irrelevant (for example the transformation doesn't need to be reversible). That becomes a different question, so I'll leave it there.
I find that simple XOR encryption is best suited for URL obfuscation. You can continue using whatever serial number you are using without change. Further XOR encryption doesn't increase the length of source string. If your text is 22 bytes, the encrypted string will be 22 bytes too. It's not easy enough as to be guessed like rot 13 but not heavy weight like DSE/RSA.
Search the net for PHP XOR encryption to find some implementation. The first one I found is here.
I've toyed with this sort of thing myself, in my amateurish way, and arrived at a kind of kooky number scrambling algorithm, involving mixed radices. Basically I have a function that maps a number between 0-N to another number in the 0-N range. For URLS I then map that number to a couple of english words. (words are easier to remember).
A simplified version of what I do, without mixed radices: You have a number that is 32 bits, so ahead of time, have a passkey which is 32-bits long, and XOR the passkey with your input number. Then shuffle the bits around in a determinate reordering. (possibly based on your passkey).
The nice thing about this is
No collisions, as long as you shuffle and xor the same way each time
No need to store the obfuscated keys in the database
Still use your ordered IDS internally, since you can reverse the obfuscation
You can repeat the operation several times to get more obfuscated results.
if you're up for the mixed radix version, it's basically the same, except that I add the steps of converting the input to a mixed raddix number, using the maximum range's prime factors as the digit's bases. Then I shuffle the digits around, keeping the bases with the digits, and turn it back into a standard integer.
You might find it useful to revisit the idea of using a GUID, because you can construct GUIDs in a way that isn't subject to collision.
Check out the Wikipedia page on GUIDs - the "Type 1" algorithm uses both the MAC address of the PC, and the current date/time as inputs. This guarantees that collisions are simply impossible.
Alternatively, if you create a GUID column in your database as an alternative-key (keep using your auto-increment primary keys), define it as unique. Then, if your GUID generation approach does give a duplicate, you'll get an appropriate error on insert that you can handle.
I saw this question yesterday: how reddit generates an alphanum id
I think it's a reasonably good method (and particularily clever)
it uses Python
def to_base(q, alphabet):
if q < 0: raise ValueError, "must supply a positive integer"
l = len(alphabet)
converted = []
while q != 0:
q, r = divmod(q, l)
converted.insert(0, alphabet[r])
return "".join(converted) or '0'
def to36(q):
return to_base(q, '0123456789abcdefghijklmnopqrstuvwxyz')
Add a char(10) field to your order table... call it 'order_number'.
After you create a new order, randomly generate an integer from 1...9999999999. Check to see if it exists in the database under 'order_number'. If not, update your latest row with this value. If it does exist, pick another number at random.
Use 'order_number' for publicly viewable URLs, maybe always padded with zeros.
There's a race condition concern for when two threads attempt to add the same number at the same time... you could do a table lock if you were really concerned, but that's a big hammer. Add a second check after updating, re-select to ensure it's unique. Call recursively until you get a unique entry. Dwell for a random number of milliseconds between calls, and use the current time as a seed for the random number generator.
Swiped from here.
UPDATED As with using the GUID aproach described by Bevan, if the column is constrained as unique, then you don't have to sweat it. I guess this is no different that using a GUID, except that the customer and Customer Service will have an easier time referring to the order.
I've found a much simpler way. Say you want to map N digits, pseudorandomly to N digits. you find the next highest prime from N, and you make your function
prandmap(x) return x * nextPrime(N) % N
this will produce a function that repeats (or has a period) every N, no number is produced twice until x=N+1. It always starts at 0, but is pseudorandom thereafter.
I honestly thing encrypting/decrypting query string data is a bad approach to this problem. The easiest solution is sending data using POST instead of GET. If users are clicking on links with querystring data, you have to resort to some javascript hacks to send data by POST (keep accessibility in mind for users with Javascript turned off). This doesn't prevent users from viewing source, but at the very least it keeps sensitive from being indexed by search engines, assuming the data you're trying to hide really that sensitive in the first place.
Another approach is to use a natural unique key. For example, if you're issuing invoices to customers on a monthly basis, then "yyyyMM[customerID]" uniquely identifies a particular invoice for a particular user.
From your description, personally, I would start off by working with whatever standard encryption library is available (I'm a Java programmer, but I assume, say, a basic AES encryption library must be available for PHP):
on the database, just key things as you normally would
whenever you need to transmit a key to/from a client, use a fairly strong, standard encryption system (e.g. AES) to convert the key to/from a string of garbage. As your plain text, use a (say) 128-byte buffer containing: a (say) 4-byte key, 60 random bytes, and then a 64-byte medium-quality hash of the previous 64 bytes (see Numerical Recipes for an example)-- obviously when you receive such a string, you decrypt it then check if the hash matches before hitting the DB. If you're being a bit more paranoid, send an AES-encrypted buffer of random bytes with your key in an arbitrary position, plus a secure hash of that buffer as a separate parameter. The first option is probably a reasonable tradeoff between performance and security for your purposes, though, especially when combined with other security measures.
the day that you're processing so many invoices a second that AES encrypting them in transit is too performance expensive, go out and buy yourself a big fat server with lots of CPUs to celebrate.
Also, if you want to hide that the variable is an invoice ID, you might consider calling it something other than "invoice_id".
I have recently run across these terms few times but I am quite confused how they work and when they are usualy implemented?
Well, think of it this way.
If you use an array, a simple index-based data structure, and fill it up with random stuff, finding a particular entry gets to be a more and more expensive operation as you fill it with data, since you basically have to start searching from one end toward the other, until you find the one you want.
If you want to get faster access to data, you typicall resort to sorting the array and using a binary search. This, however, while increasing the speed of looking up an existing value, makes inserting new values slow, as you need to move existing elements around when you need to insert an element in the middle.
A hashtable, on the other hand, has an associated function that takes an entry, and reduces it to a number, a hash-key. This number is then used as an index into the array, and this is where you store the entry.
A hashtable revolves around an array, which initially starts out empty. Empty does not mean zero length, the array starts out with a size, but all the elements in the array contains nothing.
Each element has two properties, data, and a key that identifies the data. For instance, a list of zip-codes of the US would be a zip-code -> name type of association. The function reduces the key, but does not consider the data.
So when you insert something into the hashtable, the function reduces the key to a number, which is used as an index into this (empty) array, and this is where you store the data, both the key, and the associated data.
Then, later, you want to find a particular entry that you know the key for, so you run the key through the same function, get its hash-key, and goes to that particular place in the hashtable and retrieves the data there.
The theory goes that the function that reduces your key to a hash-key, that number, is computationally much cheaper than the linear search.
A typical hashtable does not have an infinite number of elements available for storage, so the number is typically reduced further down to an index which fits into the size of the array. One way to do this is to simply take the modulus of the index compared to the size of the array. For an array with a size of 10, index 0-9 will map directly to an index, and index 10-19 will map down to 0-9 again, and so on.
Some keys will be reduced to the same index as an existing entry in the hashtable. At this point the actual keys are compared directly, with all the rules associated with comparing the data types of the key (ie. normal string comparison for instance). If there is a complete match, you either disregard the new data (it already exists) or you overwrite (you replace the old data for that key), or you add it (multi-valued hashtable). If there is no match, which means that though the hash keys was identical, the actual keys were not, you typically find a new location to store that key+data in.
Collision resolution has many implementations, and the simplest one is to just go to the next empty element in the array. This simple solution has other problems though, so finding the right resolution algorithm is also a good excercise for hashtables.
Hashtables can also grow, if they fill up completely (or close to), and this is usually done by creating a new array of the new size, and calculating all the indexes once more, and placing the items into the new array in their new locations.
The function that reduces the key to a number does not produce a linear value, ie. "AAA" becomes 1, then "AAB" becomes 2, so the hashtable is not sorted by any typical value.
There is a good wikipedia article available on the subject as well, here.
lassevk's answer is very good, but might contain a little too much detail. Here is the executive summary. I am intentionally omitting certain relevant information which you can safely ignore 99% of the time.
There is no important difference between hash tables and hash maps 99% of the time.
Hash tables are magic
Seriously. Its a magic data structure which all but guarantees three things. (There are exceptions. You can largely ignore them, although learning them someday might be useful for you.)
1) Everything in the hash table is part of a pair -- there is a key and a value. You put in and get out data by specifying the key you are operating on.
2) If you are doing anything by a single key on a hash table, it is blazingly fast. This implies that put(key,value), get(key), contains(key), and remove(key) are all really fast.
3) Generic hash tables fail at doing anything not listed in #2! (By "fail", we mean they are blazingly slow.)
When do we use hash tables?
We use hash tables when their magic fits our problem.
For example, caching frequently ends up using a hash table -- for example, let's say we have 45,000 students in a university and some process needs to hold on to records for all of them. If you routinely refer to student by ID number, then a ID => student cache makes excellent sense. The operation you are optimizing for this cache is fast lookup.
Hashes are also extraordinarily useful for storing relationships between data when you don't want to go whole hog and alter the objects themselves. For example, during course registration, it might be a good idea to be able to relate students to the classes they are taking. However, for whatever reason you might not want the Student object itself to know about that. Use a studentToClassRegistration hash and keep it around while you do whatever it is you need to do.
They also make a fairly good first choice for a data structure except when you need to do one of the following:
When Not To Use Hash Tables
Iterate over the elements. Hash tables typically do not do iteration very well. (Generic ones, that is. Particular implementations sometimes contain linked lists which are used to make iterating over them suck less. For example, in Java, LinkedHashMap lets you iterate over keys or values quickly.)
Sorting. If you can't iterate, sorting is a royal pain, too.
Going from value to key. Use two hash tables. Trust me, I just saved you a lot of pain.
if you are talking in terms of Java, both are collections which allow objects addition, deletion and updation and use Hasing algorithms internally.
The significant difference however, if we talk in reference to Java, is that hashtables are inherently synchronized and hence are thread safe while the hash maps are not thread safe collection.
Apart from the synchronization, the internal mechanism to store and retrieve objects is hashing in both the cases.
If you need to see how Hashing works, I would recommend a bit of googling on Data Structers and hashing techniques.
Hashtables/hashmaps associate a value (called 'key' for disambiguation purposes) with another value. You can think them as kind of a dictionary (word: definition) or a database record (key: data).