2005-04-17 06:20:36 +08:00
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/*
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* include/linux/random.h
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*
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* Include file for the random number generator.
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*/
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#ifndef _LINUX_RANDOM_H
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#define _LINUX_RANDOM_H
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2012-10-13 17:46:48 +08:00
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#include <uapi/linux/random.h>
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2005-04-17 06:20:36 +08:00
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2012-07-04 23:16:01 +08:00
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extern void add_device_randomness(const void *, unsigned int);
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2005-04-17 06:20:36 +08:00
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extern void add_input_randomness(unsigned int type, unsigned int code,
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unsigned int value);
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2012-07-02 19:52:16 +08:00
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extern void add_interrupt_randomness(int irq, int irq_flags);
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2005-04-17 06:20:36 +08:00
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extern void get_random_bytes(void *buf, int nbytes);
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random: add new get_random_bytes_arch() function
Create a new function, get_random_bytes_arch() which will use the
architecture-specific hardware random number generator if it is
present. Change get_random_bytes() to not use the HW RNG, even if it
is avaiable.
The reason for this is that the hw random number generator is fast (if
it is present), but it requires that we trust the hardware
manufacturer to have not put in a back door. (For example, an
increasing counter encrypted by an AES key known to the NSA.)
It's unlikely that Intel (for example) was paid off by the US
Government to do this, but it's impossible for them to prove otherwise
--- especially since Bull Mountain is documented to use AES as a
whitener. Hence, the output of an evil, trojan-horse version of
RDRAND is statistically indistinguishable from an RDRAND implemented
to the specifications claimed by Intel. Short of using a tunnelling
electronic microscope to reverse engineer an Ivy Bridge chip and
disassembling and analyzing the CPU microcode, there's no way for us
to tell for sure.
Since users of get_random_bytes() in the Linux kernel need to be able
to support hardware systems where the HW RNG is not present, most
time-sensitive users of this interface have already created their own
cryptographic RNG interface which uses get_random_bytes() as a seed.
So it's much better to use the HW RNG to improve the existing random
number generator, by mixing in any entropy returned by the HW RNG into
/dev/random's entropy pool, but to always _use_ /dev/random's entropy
pool.
This way we get almost of the benefits of the HW RNG without any
potential liabilities. The only benefits we forgo is the
speed/performance enhancements --- and generic kernel code can't
depend on depend on get_random_bytes() having the speed of a HW RNG
anyway.
For those places that really want access to the arch-specific HW RNG,
if it is available, we provide get_random_bytes_arch().
Signed-off-by: "Theodore Ts'o" <tytso@mit.edu>
Cc: stable@vger.kernel.org
2012-07-05 22:35:23 +08:00
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extern void get_random_bytes_arch(void *buf, int nbytes);
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2005-04-17 06:20:36 +08:00
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void generate_random_uuid(unsigned char uuid_out[16]);
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2013-09-10 22:52:35 +08:00
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extern int random_int_secret_init(void);
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2005-04-17 06:20:36 +08:00
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#ifndef MODULE
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2007-02-12 16:55:28 +08:00
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extern const struct file_operations random_fops, urandom_fops;
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2005-04-17 06:20:36 +08:00
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#endif
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unsigned int get_random_int(void);
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unsigned long randomize_range(unsigned long start, unsigned long end, unsigned long len);
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2012-12-18 08:04:23 +08:00
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u32 prandom_u32(void);
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2012-12-18 08:04:25 +08:00
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void prandom_bytes(void *buf, int nbytes);
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2012-12-18 08:04:23 +08:00
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void prandom_seed(u32 seed);
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2013-11-11 19:20:34 +08:00
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void prandom_reseed_late(void);
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2006-10-17 15:09:42 +08:00
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2013-11-11 19:20:35 +08:00
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struct rnd_state {
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random32: upgrade taus88 generator to taus113 from errata paper
Since we use prandom*() functions quite often in networking code
i.e. in UDP port selection, netfilter code, etc, upgrade the PRNG
from Pierre L'Ecuyer's original paper "Maximally Equidistributed
Combined Tausworthe Generators", Mathematics of Computation, 65,
213 (1996), 203--213 to the version published in his errata paper [1].
The Tausworthe generator is a maximally-equidistributed generator,
that is fast and has good statistical properties [1].
The version presented there upgrades the 3 state LFSR to a 4 state
LFSR with increased periodicity from about 2^88 to 2^113. The
algorithm is presented in [1] by the very same author who also
designed the original algorithm in [2].
Also, by increasing the state, we make it a bit harder for attackers
to "guess" the PRNGs internal state. See also discussion in [3].
Now, as we use this sort of weak initialization discussed in [3]
only between core_initcall() until late_initcall() time [*] for
prandom32*() users, namely in prandom_init(), it is less relevant
from late_initcall() onwards as we overwrite seeds through
prandom_reseed() anyways with a seed source of higher entropy, that
is, get_random_bytes(). In other words, a exhaustive keysearch of
96 bit would be needed. Now, with the help of this patch, this
state-search increases further to 128 bit. Initialization needs
to make sure that s1 > 1, s2 > 7, s3 > 15, s4 > 127.
taus88 and taus113 algorithm is also part of GSL. I added a test
case in the next patch to verify internal behaviour of this patch
with GSL and ran tests with the dieharder 3.31.1 RNG test suite:
$ dieharder -g 052 -a -m 10 -s 1 -S 4137730333 #taus88
$ dieharder -g 054 -a -m 10 -s 1 -S 4137730333 #taus113
With this seed configuration, in order to compare both, we get
the following differences:
algorithm taus88 taus113
rands/second [**] 1.61e+08 1.37e+08
sts_serial(4, 1st run) WEAK PASSED
sts_serial(9, 2nd run) WEAK PASSED
rgb_lagged_sum(31) WEAK PASSED
We took out diehard_sums test as according to the authors it is
considered broken and unusable [4]. Despite that and the slight
decrease in performance (which is acceptable), taus113 here passes
all 113 tests (only rgb_minimum_distance_5 in WEAK, the rest PASSED).
In general, taus/taus113 is considered "very good" by the authors
of dieharder [5].
The papers [1][2] states a single warm-up step is sufficient by
running quicktaus once on each state to ensure proper initialization
of ~s_{0}:
Our selection of (s) according to Table 1 of [1] row 1 holds the
condition L - k <= r - s, that is,
(32 32 32 32) - (31 29 28 25) <= (25 27 15 22) - (18 2 7 13)
with r = k - q and q = (6 2 13 3) as also stated by the paper.
So according to [2] we are safe with one round of quicktaus for
initialization. However we decided to include the warm-up phase
of the PRNG as done in GSL in every case as a safety net. We also
use the warm up phase to make the output of the RNG easier to
verify by the GSL output.
In prandom_init(), we also mix random_get_entropy() into it, just
like drivers/char/random.c does it, jiffies ^ random_get_entropy().
random-get_entropy() is get_cycles(). xor is entropy preserving so
it is fine if it is not implemented by some architectures.
Note, this PRNG is *not* used for cryptography in the kernel, but
rather as a fast PRNG for various randomizations i.e. in the
networking code, or elsewhere for debugging purposes, for example.
[*]: In order to generate some "sort of pseduo-randomness", since
get_random_bytes() is not yet available for us, we use jiffies and
initialize states s1 - s3 with a simple linear congruential generator
(LCG), that is x <- x * 69069; and derive s2, s3, from the 32bit
initialization from s1. So the above quote from [3] accounts only
for the time from core to late initcall, not afterwards.
[**] Single threaded run on MacBook Air w/ Intel Core i5-3317U
[1] http://www.iro.umontreal.ca/~lecuyer/myftp/papers/tausme2.ps
[2] http://www.iro.umontreal.ca/~lecuyer/myftp/papers/tausme.ps
[3] http://thread.gmane.org/gmane.comp.encryption.general/12103/
[4] http://code.google.com/p/dieharder/source/browse/trunk/libdieharder/diehard_sums.c?spec=svn490&r=490#20
[5] http://www.phy.duke.edu/~rgb/General/dieharder.php
Joint work with Hannes Frederic Sowa.
Cc: Florian Weimer <fweimer@redhat.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Daniel Borkmann <dborkman@redhat.com>
Signed-off-by: Hannes Frederic Sowa <hannes@stressinduktion.org>
Signed-off-by: David S. Miller <davem@davemloft.net>
2013-11-11 19:20:36 +08:00
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__u32 s1, s2, s3, s4;
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2013-11-11 19:20:35 +08:00
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};
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random32: upgrade taus88 generator to taus113 from errata paper
Since we use prandom*() functions quite often in networking code
i.e. in UDP port selection, netfilter code, etc, upgrade the PRNG
from Pierre L'Ecuyer's original paper "Maximally Equidistributed
Combined Tausworthe Generators", Mathematics of Computation, 65,
213 (1996), 203--213 to the version published in his errata paper [1].
The Tausworthe generator is a maximally-equidistributed generator,
that is fast and has good statistical properties [1].
The version presented there upgrades the 3 state LFSR to a 4 state
LFSR with increased periodicity from about 2^88 to 2^113. The
algorithm is presented in [1] by the very same author who also
designed the original algorithm in [2].
Also, by increasing the state, we make it a bit harder for attackers
to "guess" the PRNGs internal state. See also discussion in [3].
Now, as we use this sort of weak initialization discussed in [3]
only between core_initcall() until late_initcall() time [*] for
prandom32*() users, namely in prandom_init(), it is less relevant
from late_initcall() onwards as we overwrite seeds through
prandom_reseed() anyways with a seed source of higher entropy, that
is, get_random_bytes(). In other words, a exhaustive keysearch of
96 bit would be needed. Now, with the help of this patch, this
state-search increases further to 128 bit. Initialization needs
to make sure that s1 > 1, s2 > 7, s3 > 15, s4 > 127.
taus88 and taus113 algorithm is also part of GSL. I added a test
case in the next patch to verify internal behaviour of this patch
with GSL and ran tests with the dieharder 3.31.1 RNG test suite:
$ dieharder -g 052 -a -m 10 -s 1 -S 4137730333 #taus88
$ dieharder -g 054 -a -m 10 -s 1 -S 4137730333 #taus113
With this seed configuration, in order to compare both, we get
the following differences:
algorithm taus88 taus113
rands/second [**] 1.61e+08 1.37e+08
sts_serial(4, 1st run) WEAK PASSED
sts_serial(9, 2nd run) WEAK PASSED
rgb_lagged_sum(31) WEAK PASSED
We took out diehard_sums test as according to the authors it is
considered broken and unusable [4]. Despite that and the slight
decrease in performance (which is acceptable), taus113 here passes
all 113 tests (only rgb_minimum_distance_5 in WEAK, the rest PASSED).
In general, taus/taus113 is considered "very good" by the authors
of dieharder [5].
The papers [1][2] states a single warm-up step is sufficient by
running quicktaus once on each state to ensure proper initialization
of ~s_{0}:
Our selection of (s) according to Table 1 of [1] row 1 holds the
condition L - k <= r - s, that is,
(32 32 32 32) - (31 29 28 25) <= (25 27 15 22) - (18 2 7 13)
with r = k - q and q = (6 2 13 3) as also stated by the paper.
So according to [2] we are safe with one round of quicktaus for
initialization. However we decided to include the warm-up phase
of the PRNG as done in GSL in every case as a safety net. We also
use the warm up phase to make the output of the RNG easier to
verify by the GSL output.
In prandom_init(), we also mix random_get_entropy() into it, just
like drivers/char/random.c does it, jiffies ^ random_get_entropy().
random-get_entropy() is get_cycles(). xor is entropy preserving so
it is fine if it is not implemented by some architectures.
Note, this PRNG is *not* used for cryptography in the kernel, but
rather as a fast PRNG for various randomizations i.e. in the
networking code, or elsewhere for debugging purposes, for example.
[*]: In order to generate some "sort of pseduo-randomness", since
get_random_bytes() is not yet available for us, we use jiffies and
initialize states s1 - s3 with a simple linear congruential generator
(LCG), that is x <- x * 69069; and derive s2, s3, from the 32bit
initialization from s1. So the above quote from [3] accounts only
for the time from core to late initcall, not afterwards.
[**] Single threaded run on MacBook Air w/ Intel Core i5-3317U
[1] http://www.iro.umontreal.ca/~lecuyer/myftp/papers/tausme2.ps
[2] http://www.iro.umontreal.ca/~lecuyer/myftp/papers/tausme.ps
[3] http://thread.gmane.org/gmane.comp.encryption.general/12103/
[4] http://code.google.com/p/dieharder/source/browse/trunk/libdieharder/diehard_sums.c?spec=svn490&r=490#20
[5] http://www.phy.duke.edu/~rgb/General/dieharder.php
Joint work with Hannes Frederic Sowa.
Cc: Florian Weimer <fweimer@redhat.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Daniel Borkmann <dborkman@redhat.com>
Signed-off-by: Hannes Frederic Sowa <hannes@stressinduktion.org>
Signed-off-by: David S. Miller <davem@davemloft.net>
2013-11-11 19:20:36 +08:00
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u32 prandom_u32_state(struct rnd_state *state);
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2012-12-18 08:04:25 +08:00
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void prandom_bytes_state(struct rnd_state *state, void *buf, int nbytes);
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2010-05-27 05:44:13 +08:00
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random32: add prandom_u32_max and convert open coded users
Many functions have open coded a function that returns a random
number in range [0,N-1]. Under the assumption that we have a PRNG
such as taus113 with being well distributed in [0, ~0U] space,
we can implement such a function as uword t = (n*m')>>32, where
m' is a random number obtained from PRNG, n the right open interval
border and t our resulting random number, with n,m',t in u32 universe.
Lets go with Joe and simply call it prandom_u32_max(), although
technically we have an right open interval endpoint, but that we
have documented. Other users can further be migrated to the new
prandom_u32_max() function later on; for now, we need to make sure
to migrate reciprocal_divide() users for the reciprocal_divide()
follow-up fixup since their function signatures are going to change.
Joint work with Hannes Frederic Sowa.
Cc: Jakub Zawadzki <darkjames-ws@darkjames.pl>
Cc: Eric Dumazet <eric.dumazet@gmail.com>
Cc: linux-kernel@vger.kernel.org
Signed-off-by: Hannes Frederic Sowa <hannes@stressinduktion.org>
Signed-off-by: Daniel Borkmann <dborkman@redhat.com>
Signed-off-by: David S. Miller <davem@davemloft.net>
2014-01-22 09:29:39 +08:00
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/**
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* prandom_u32_max - returns a pseudo-random number in interval [0, ep_ro)
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* @ep_ro: right open interval endpoint
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*
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* Returns a pseudo-random number that is in interval [0, ep_ro). Note
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* that the result depends on PRNG being well distributed in [0, ~0U]
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* u32 space. Here we use maximally equidistributed combined Tausworthe
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* generator, that is, prandom_u32(). This is useful when requesting a
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* random index of an array containing ep_ro elements, for example.
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*
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* Returns: pseudo-random number in interval [0, ep_ro)
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*/
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static inline u32 prandom_u32_max(u32 ep_ro)
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{
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return (u32)(((u64) prandom_u32() * ep_ro) >> 32);
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}
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2010-05-27 05:44:13 +08:00
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/*
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* Handle minimum values for seeds
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*/
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static inline u32 __seed(u32 x, u32 m)
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{
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return (x < m) ? x + m : x;
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}
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/**
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2012-12-18 08:04:23 +08:00
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* prandom_seed_state - set seed for prandom_u32_state().
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2010-05-27 05:44:13 +08:00
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* @state: pointer to state structure to receive the seed.
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* @seed: arbitrary 64-bit value to use as a seed.
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*/
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2012-12-18 08:04:23 +08:00
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static inline void prandom_seed_state(struct rnd_state *state, u64 seed)
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2010-05-27 05:44:13 +08:00
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{
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u32 i = (seed >> 32) ^ (seed << 10) ^ seed;
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random32: upgrade taus88 generator to taus113 from errata paper
Since we use prandom*() functions quite often in networking code
i.e. in UDP port selection, netfilter code, etc, upgrade the PRNG
from Pierre L'Ecuyer's original paper "Maximally Equidistributed
Combined Tausworthe Generators", Mathematics of Computation, 65,
213 (1996), 203--213 to the version published in his errata paper [1].
The Tausworthe generator is a maximally-equidistributed generator,
that is fast and has good statistical properties [1].
The version presented there upgrades the 3 state LFSR to a 4 state
LFSR with increased periodicity from about 2^88 to 2^113. The
algorithm is presented in [1] by the very same author who also
designed the original algorithm in [2].
Also, by increasing the state, we make it a bit harder for attackers
to "guess" the PRNGs internal state. See also discussion in [3].
Now, as we use this sort of weak initialization discussed in [3]
only between core_initcall() until late_initcall() time [*] for
prandom32*() users, namely in prandom_init(), it is less relevant
from late_initcall() onwards as we overwrite seeds through
prandom_reseed() anyways with a seed source of higher entropy, that
is, get_random_bytes(). In other words, a exhaustive keysearch of
96 bit would be needed. Now, with the help of this patch, this
state-search increases further to 128 bit. Initialization needs
to make sure that s1 > 1, s2 > 7, s3 > 15, s4 > 127.
taus88 and taus113 algorithm is also part of GSL. I added a test
case in the next patch to verify internal behaviour of this patch
with GSL and ran tests with the dieharder 3.31.1 RNG test suite:
$ dieharder -g 052 -a -m 10 -s 1 -S 4137730333 #taus88
$ dieharder -g 054 -a -m 10 -s 1 -S 4137730333 #taus113
With this seed configuration, in order to compare both, we get
the following differences:
algorithm taus88 taus113
rands/second [**] 1.61e+08 1.37e+08
sts_serial(4, 1st run) WEAK PASSED
sts_serial(9, 2nd run) WEAK PASSED
rgb_lagged_sum(31) WEAK PASSED
We took out diehard_sums test as according to the authors it is
considered broken and unusable [4]. Despite that and the slight
decrease in performance (which is acceptable), taus113 here passes
all 113 tests (only rgb_minimum_distance_5 in WEAK, the rest PASSED).
In general, taus/taus113 is considered "very good" by the authors
of dieharder [5].
The papers [1][2] states a single warm-up step is sufficient by
running quicktaus once on each state to ensure proper initialization
of ~s_{0}:
Our selection of (s) according to Table 1 of [1] row 1 holds the
condition L - k <= r - s, that is,
(32 32 32 32) - (31 29 28 25) <= (25 27 15 22) - (18 2 7 13)
with r = k - q and q = (6 2 13 3) as also stated by the paper.
So according to [2] we are safe with one round of quicktaus for
initialization. However we decided to include the warm-up phase
of the PRNG as done in GSL in every case as a safety net. We also
use the warm up phase to make the output of the RNG easier to
verify by the GSL output.
In prandom_init(), we also mix random_get_entropy() into it, just
like drivers/char/random.c does it, jiffies ^ random_get_entropy().
random-get_entropy() is get_cycles(). xor is entropy preserving so
it is fine if it is not implemented by some architectures.
Note, this PRNG is *not* used for cryptography in the kernel, but
rather as a fast PRNG for various randomizations i.e. in the
networking code, or elsewhere for debugging purposes, for example.
[*]: In order to generate some "sort of pseduo-randomness", since
get_random_bytes() is not yet available for us, we use jiffies and
initialize states s1 - s3 with a simple linear congruential generator
(LCG), that is x <- x * 69069; and derive s2, s3, from the 32bit
initialization from s1. So the above quote from [3] accounts only
for the time from core to late initcall, not afterwards.
[**] Single threaded run on MacBook Air w/ Intel Core i5-3317U
[1] http://www.iro.umontreal.ca/~lecuyer/myftp/papers/tausme2.ps
[2] http://www.iro.umontreal.ca/~lecuyer/myftp/papers/tausme.ps
[3] http://thread.gmane.org/gmane.comp.encryption.general/12103/
[4] http://code.google.com/p/dieharder/source/browse/trunk/libdieharder/diehard_sums.c?spec=svn490&r=490#20
[5] http://www.phy.duke.edu/~rgb/General/dieharder.php
Joint work with Hannes Frederic Sowa.
Cc: Florian Weimer <fweimer@redhat.com>
Cc: Theodore Ts'o <tytso@mit.edu>
Signed-off-by: Daniel Borkmann <dborkman@redhat.com>
Signed-off-by: Hannes Frederic Sowa <hannes@stressinduktion.org>
Signed-off-by: David S. Miller <davem@davemloft.net>
2013-11-11 19:20:36 +08:00
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state->s1 = __seed(i, 2U);
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state->s2 = __seed(i, 8U);
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state->s3 = __seed(i, 16U);
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state->s4 = __seed(i, 128U);
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2010-05-27 05:44:13 +08:00
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}
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2011-08-01 04:54:50 +08:00
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#ifdef CONFIG_ARCH_RANDOM
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# include <asm/archrandom.h>
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#else
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static inline int arch_get_random_long(unsigned long *v)
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{
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return 0;
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}
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static inline int arch_get_random_int(unsigned int *v)
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{
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return 0;
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}
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#endif
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2013-01-22 17:49:50 +08:00
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/* Pseudo random number generator from numerical recipes. */
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static inline u32 next_pseudo_random32(u32 seed)
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{
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return seed * 1664525 + 1013904223;
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}
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2005-04-17 06:20:36 +08:00
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#endif /* _LINUX_RANDOM_H */
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