1 Multiprecision maths library
4 Catacomb comes with a fairly reasonable multiprecision maths
5 library. It's not stunningly fast, and doesn't do everything,
6 but it seems good for the sorts of things needed in
7 cryptographic algorithms (which, for example, GMP isn't[1]).
9 There are basically three layers to the system:
11 * The low-level `mpx' layer, which implements some basic
12 arithmetic but is fairly unpleasant to actually use.
14 * A high-level `mp' layer, which provides a useful `mp'
15 multiprecision type and implements useful arithmetic on
18 * Everything else. A collection of miscellaneous routines for
19 performing particular operations efficiently or simply.
21 [1] In particular, GMP is truly rotten at converting numbers
22 into well-defined binary formats. It has its own format,
23 but it's not defined in the manual, has changed once before,
24 probably doesn't conform to any standards in the
25 cryptographic community, and can only be written to or read
26 from a file stream, so you can't use it in memory (for
27 example to encrypt it). Basically, it's a right pain.
30 The low-level interface
32 The low level is described in `mpx.h'. It includes everything
35 An integer is represented in an array of words. Each word has
36 type `mpw' (multi precision word). The least significant word
37 comes first. An array is described by its `base' -- the address
38 of the first element -- and its `limit' -- the address *just
39 after* the last element. Thus, the length of the array is
40 `limit - base'. This representation is particularly convenient
41 for many things. An old version used base and length, which was
44 The largest value which can be represented in a word is
45 MPW_MAX. The number of bits used in the representation of a
46 word is MPW_BITS. Actually, you might be able to use more bits
47 and store larger numbers, but everything will go wrong if you
50 The macro call MPW(x) returns the low MPW_BITS bits of x. It's
51 very useful in low-level arithmetic.
53 The call MPWS(n) tells you the `sizeof' an array of n words.
54 It's also very useful. Try not to get MPW and MPWS confused
55 because they mean very different things.
57 The actual low-level macros and functions are documented
58 relatively well. They are given source and destination arrays
59 for things to be read and written to. Usually the sources
60 mustn't overlap the destinations, and destinations certainly
61 mustn't overlap other destinations; sometimes this restriction
62 is lifted, where it would be both convenient and easy to do so.
63 Sources can overlap each other without problems, because they're
66 The difficult parts are the Karatsuba functions. Karatsuba
67 and Ofman discovered a neat recursive way to multiply large
68 numbers. It requires quite a bit of workspace, and adds some
69 overhead, but has lower asymptotic complexity than the standard
70 multiply algorithm. Usually, Karatsuba functions get used
71 automatically by the rest of the library when appropriate and
72 you don't have to care.
75 The high-level interface
77 The high-level invents a type, `mp'. It's a structured type,
78 with the following members:
80 mpw *v, *vl Base and limit of the word array.
81 size_t sz Number of words actually allocated to the array.
82 unsigned f Various flags.
83 unsigned ref Number of references to the integer.
85 The flags are interesting. Here's what they mean:
87 MP_NEG The number is negative
88 MP_BURN Burn the number after using it
89 MP_CONST The number mustn't be modified or freed
90 MP_UNDEF The number contains no interesting value
91 MP_DESTROYED The number has been freed once already
93 The last one is handy for catching bugs. MP_NEG is obvious --
94 Catacomb uses a signed-magnitude representation because things
95 are usually easier that way. MP_CONST is set on various
96 constants provided for general convenience so they don't get
97 destroyed by accident. MP_UNDEF is used to avoid copying
100 MP_BURN marks a `secret' number. Secret numbers are overwritten
101 with zeroes (`burnt') when they're freed. Secrecy is a viral
102 concept: anything calculated from a secret number is also
103 secret, so they get burnt too.
105 Most of the time, you refer to numbers by their addresses. Lots
106 of `mp *' pointers get used. You hardly ever see a real `mp',
107 just pointers to them.
109 There are a collection of utility functions for keeping the
110 system running -- for creating new numbers without interesting
111 values, for throwing old ones away, for extending the amount of
112 memory they use, and so on.
114 Throwing numbers away is simple. You pass the pointer to the
115 number to `mp_drop'. If someone else still has a reference to
116 the number, it stays where it is, but remembers that you're not
117 interested in it any more. If nobody's interested then the
118 number is disposed of.
120 You can add a reference using MP_COPY. It returns the new
121 reference. The new reference is the same as the old one, but
122 it's a useful fiction to pretend that it's different.
124 Real arithmetic happens in a fairly uniform way. There's an
125 important point to make about `destinations', though. Just
126 about all of the arithmetic functions take `destination'
127 arguments (one for each result), with the idea that, at least
128 conceptually, they store the results there. What actually
129 happens is that a reference is lost to whatever the destination
130 used to refer to, and a reference to the new result is gained.
131 The address might be different, and then again it might not.
132 Destinations can be the same as sources -- that works fine.
133 Finally, there's the magic value `MP_NEW'. MP_NEW is a special
134 constant which, as a destination, means `create a new place and
135 put the answer there'.
137 The idea is that, sometimes it helps that memory is already
138 allocated for a destination, so it doesn't have to be obtained
139 specially, and, even more often, you want to throw away old
140 intermediate results while you're calculating new ones.
142 Here are some examples of how to do it right:
144 x = mp_add(MP_NEW, y, z);
145 Assumes x didn't have a useful value before.
146 Afterwards it refers to the sum of y and z. y and z
147 themselves are unchanged.
150 Add z to y. Now y is the sum of z and the old y. z is
154 mp_div(&q, &x, x, y);
155 Sets q (a new value) equal to x / y, and puts the
156 remainder back in x. y is unchanged.
159 Subtract z from y, putting the result back in z. y is
163 Multiply y by z, putting the result in x, but making y
166 Here are some examples of how to do it wrong:
169 mp_mul might choose somewhere other than y's storage to
170 write its result. (In fact, the current version
171 certainly will.) So y is trashed because there are no
172 references to it any more, and the result of the
173 multiplication is lost.
177 Whoops. We stored the result in x, but y still got
178 trashed and might contain anything. Adding it to x is a
181 It's not hard once you get the hang of it, although it might
182 feel a bit weird to start with.
185 Modular multiplication and exponentiation
187 Lots of public-key crypto uses modular multiplication and
188 exponentiation operations. Doing them efficiently is very
189 important. Multiplication on its own is easy, and Catacomb's
190 multiplication algorithms are fairly good (though not up with
191 the very best). Doing the modular reduction afterwards is the
194 There are three approaches to modular reduction in Catacomb.
195 All of them have their good and bad points.
199 For a one-off calculation, this is a good idea. Division is a
200 slow operation -- that's a shame, but life's like that. But
201 when you're doing a one-shot operation, that's the best you can
204 2. Use Barrett reduction
206 Barrett reduction is a system whereby you do a little
207 precomputation up-front (one division, in fact) and are then
208 able to perform modular reductions without resorting to
209 expensive division operations. To use it, you initialize a
210 `context' with the modulus, reduce some numbers, and then
211 destroy the context when you've finished.
213 Conceptually, Barrett reduction is simple. You give it x and it
214 gives you back x mod m. The mathematics behind it is fairly
215 clever, though -- the real manual has a page of explanation for
218 Barrett reduction works on any positive modulus m. It will do a
219 modular reduction on any integer x which is at most twice as
220 long as m (in words). x can be larger than m^2, but it mustn't
221 be more than twice as long.
223 3. Use Montgomery reduction
225 Montgomery reduction is a little more clever. It does a little
226 more work up-front than Barrett reduction, and understanding the
227 benefits is a little harder. However, it's actually slightly
228 more efficient for general use. There's also a disadvantage
229 that Montgomery reduction only works when the modulus is *odd*.
230 It all goes horribly wrong with an even modulus. Don't try it.
232 I'm not going to explain how Montgomery reduction actually
233 works. But I am going to explain how to use it.
235 The precomputation for Montgomery reduction, performed when you
236 initialize a context, computes a value called R, and also R^2
237 (both mod m). (It also computes some other stuff, but that's
238 not important for this discussion.) Note that R is dependent on
241 A Montgomery reduction takes a number x, which should be less
242 than m^2 (it can actually be a bit larger) and computes the
243 value x R^{-1} mod m. That doesn't sound very useful, does it?
245 Things start looking more hopeful when you multiply your inputs
246 by R. (There's a clever way of doing that: see below.) To
247 compute xy mod m, you can first calculate xR and yR, multiply
248 them together to get xyR^2, and do a Montgomery reduction to get
249 xyR^2 R^{-1} mod m. Then the R^{-1} cancels one of the Rs and
250 you end up with xyR mod m. Essentially, you do your entire
251 calculation with an extra factor of R all the way through it.
253 Removing the factor of R at the end is easy. You just run the
254 Montgomery reduction algorithm again -- the R^{-1} cancels the R
255 and the answer pops out the end. Getting the factor of R in the
256 first place is easy -- you multiply by R^2 and do a reduction.
258 The multiply-and-reduce thing is so common that there's a
259 dedicated function which does them both in one go.
261 Here's a simple example of multiplying two numbers mod m:
265 mpmont_create(&mm, m);
266 ar = mpmont_mul(MP_NEW, a, m.r2); /* aR mod m */
267 br = mpmont_mul(MP_NEW, b, m.r2); /* bR mod m */
268 p = mpmont_mul(&mm, MP_NEW, ar, br); /* abR mod m */
269 p = mpmont_reduce(&mm, p, p); /* ab mod m */
274 Actually, it's not a very clever example. Here's a better way,
275 for such a simple calculation:
279 mpmont_create(&mm, m);
280 p = mpmont_mul(&mm, MP_NEW, a, b); /* abR^{-1} mod m */
281 p = mpmont_mul(&mm, p, p, mm.r2); /* ab mod m */
284 Of course, for a single multiply-and-reduce, you're better off
287 mp *p = mp_mul(MP_NEW, a, b);
290 the traditional division method.
292 Both Barrett and Montgomery reduction methods have modular
293 exponentiation functions. If m is a message, n is an RSA
294 modulus, and e is the public exponent, I can do an RSA
295 encryption simply by doing
298 mpmont_create(&mm, n); /* RSA modulus is odd */
299 c = mpmont_exp(&mm, MP_NEW, m, e);
302 (Yes, it's well worth creating a Montgomery context for a
303 full-blown exponentiation, unless someone's deliberately gone
304 out of their way to make it easy for you by choosing a very
305 small public exponent.)
307 RSA decryption is fully covered by the library, because doing it
308 properly is complicated and difficult since it involves playing
309 with blinding factors and the Chinese Remainder Theorem.
311 (There's also a useful RSA parameter recovery system which can
312 determine all the useful bits of information for efficient RSA
313 decryption given a very small amount of information. For
314 example, given the modulus and both exponents, it can recover
315 the two secret factors. This is, by the way, a good reason not
316 to share a modulus among many users.)
319 Finding prime numbers
321 Prime numbers are important too. Finding them is not ever-so
322 easy. There's a huge variety of useful properties which are
323 needed, and it's basically impossible to cover everything.
325 Catacomb has two useful facilities. There's a fast sequential-
326 search filtering system called `pfilt', and a good (but
327 probabilistic) primality tester which implements the Rabin-
330 Over the top of this is a configurable plug-in-appropriate-bits
331 system called `pgen' which ties everything together. You're
332 much better off using `pgen' than grovelling about with the
333 filter and Rabin-Miller tests by hand. The low-level details
334 are much better used to create new `pgen' components.
339 This basically concludes the tour of Catacomb's multiprecision
340 maths library. I hope it's provided enough background that the
341 comments start making sense.
projects / u / mdw / catacomb / blob