如果您需要128个安全随机位，符合RFC 1750的解决方案是读取已知可以生成可用熵位的硬件源(例如旋转磁盘)。更好的是，好的实现应该使用混合函数组合多个源，并最终通过重新映射或删除输出来消除输出分布的倾斜。

如果你需要更多的比特，你需要做的就是从128个安全随机比特的序列开始，并将其拉伸到所需的长度，将其映射到人类可读的文本等等。

如果你想在C中生成一个安全的随机数，我将遵循这里的源代码:

https://wiki.sei.cmu.edu/confluence/display/c/MSC30-C.+Do+not+use+the+rand%28%29+function+for+generating+pseudorandom+numbers

注意，对于Windows bbcryptgenrandom是使用的，而不是CryptGenRandom，在过去的20年里已经变得不安全。您可以亲自确认BCryptGenRandom符合RFC 1750。

For POSIX-compliant operating systems, e.g. Ubuntu (a flavor of Linux), you can simply read from /dev/urandom or /dev/random, which is a file-like interface to a device that generates bits of entropy by combining multiple sources in an RFC 1750 compliant fashion. You can read a desired number of bytes from these "files" with read or fread just like you would any other file, but note that reads from /dev/random will block until a enough new bits of entropy are available, whereas /dev/urandom will not, which can be a security issue. You can get around that by checking the size of the available entropy pool, either my reading from entropy_avail, or by using ioctl.

下面是我的方法(围绕rand()的包装器):

我还扩展到允许min为INT_MIN而max为INT_MAX的情况，这通常不可能单独使用rand()，因为它返回从0到RAND_MAX的值，包括(1/2范围)。

像这样使用它:

const int MIN = 1;
const int MAX = 1024;
// Get a pseudo-random number between MIN and MAX, **inclusive**.
// Seeding of the pseudo-random number generator automatically occurs
// the very first time you call it.
int random_num = utils_rand(MIN, MAX);

定义和氧描述:

#include <assert.h>
#include <stdbool.h>
#include <stdlib.h>

/// \brief      Use linear interpolation to rescale, or "map" value `val` from range
///             `in_min` to `in_max`, inclusive, to range `out_min` to `out_max`, inclusive.
/// \details    Similar to Arduino's ingenious `map()` function:
///             https://www.arduino.cc/reference/en/language/functions/math/map/
///
/// TODO(gabriel): turn this into a gcc statement expression instead to prevent the potential for
/// the "double evaluation" bug. See `MIN()` and `MAX()` above.
#define UTILS_MAP(val, in_min, in_max, out_min, out_max) \
    (((val) - (in_min)) * ((out_max) - (out_min)) / ((in_max) - (in_min)) + (out_min))

/// \brief      Obtain a pseudo-random integer value between `min` and `max`, **inclusive**.
/// \details    1. If `(max - min + 1) > RAND_MAX`, then the range of values returned will be
///             **scaled** to the range `max - min + 1`, and centered over the center of the
///             range at `(min + max)/2`. Scaling the numbers means that in the case of scaling,
///             not all numbers can even be reached. However, you will still be assured to have
///             a random distribution of numbers across the full range.
///             2. Also, the first time per program run that you call this function, it will
///             automatically seed the pseudo-random number generator with your system's
///             current time in seconds.
/// \param[in]  min         The minimum pseudo-random number you'd like, inclusive. Can be positive
///                         OR negative.
/// \param[in]  max         The maximum pseudo-random number you'd like, inclusive. Can be positive
///                         OR negative.
/// \return     A pseudo-random integer value between `min` and `max`, **inclusive**.
int utils_rand(int min, int max)
{
    static bool first_run = true;
    if (first_run)
    {
        // seed the pseudo-random number generator with the seconds time the very first run
        time_t time_now_sec = time(NULL);
        srand(time_now_sec);
        first_run = false;
    }

    int range = max - min + 1;
    int random_num = rand();  // random num from 0 to RAND_MAX, inclusive

    if (range > RAND_MAX)
    {
        static_assert(
            sizeof(long int) > sizeof(int),
            "This must be true or else the below mapping/scaling may have undefined overflow "
            "and not work properly. In such a case, try casting to `long long int` instead of "
            "just `long int`, and update this static_assert accordingly.");

        random_num = UTILS_MAP((long int)random_num, (long int)0, (long int)RAND_MAX, (long int)min,
                               (long int)max);
        return random_num;
    }

    // This is presumably a faster approach than the map/scaling function above, so do this faster
    // approach below whenever you don't **have** to do the more-complicated approach above.
    random_num %= range;
    random_num += min;

    return random_num;
}

参见:

[我在写下上面的答案后发现了这个问答，但它显然非常相关，他们对非缩放范围的情况做了同样的事情]我如何从rand()中获得特定的数字范围? [我需要进一步研究和阅读这个答案-似乎有一些好的观点，保持良好的随机性不使用模量]我如何从rand()得到一个特定的数字范围? http://c-faq.com/lib/randrange.html

如果你的系统支持arc4random函数族，我建议使用它们来代替标准的rand函数。

arc4random家族包括:

uint32_t arc4random(void)
void arc4random_buf(void *buf, size_t bytes)
uint32_t arc4random_uniform(uint32_t limit)
void arc4random_stir(void)
void arc4random_addrandom(unsigned char *dat, int datlen)

Arc4random返回一个随机的32位无符号整数。

Arc4random_buf将随机内容放在参数buf: void *中。内容的数量由bytes: size_t参数决定。

Arc4random_uniform返回一个随机的32位无符号整数，它遵循规则:0 <= Arc4random_uniform (limit) < limit，其中limit也是一个32位无符号整数。

Arc4random_stir从/dev/urandom读取数据，并将数据传递给arc4random_adrandom以额外随机化它的内部随机数池。

arc4random_adrandom由arc4random_stir使用，根据传递给它的数据填充它的内部随机数池。

如果你没有这些函数，但你在Unix上，那么你可以使用下面的代码:

/* This is C, not C++ */
#include <sys/types.h>
#include <sys/stat.h>
#include <fcntl.h>
#include <errno.h>
#include <unistd.h>
#include <stdlib.h> /* exit */
#include <stdio.h> /* printf */

int urandom_fd = -2;

void urandom_init() {
  urandom_fd = open("/dev/urandom", O_RDONLY);

  if (urandom_fd == -1) {
    int errsv = urandom_fd;
    printf("Error opening [/dev/urandom]: %i\n", errsv);
    exit(1);
  }
}

unsigned long urandom() {
  unsigned long buf_impl;
  unsigned long *buf = &buf_impl;

  if (urandom_fd == -2) {
    urandom_init();
  }

  /* Read sizeof(long) bytes (usually 8) into *buf, which points to buf_impl */
  read(urandom_fd, buf, sizeof(long));
  return buf_impl;
}

urandom_init函数打开/dev/urandom设备，并将文件描述符放在urandom_fd中。

urandom函数基本上与rand调用相同，只是更安全，并且它返回一个长(容易更改)。

但是，/dev/urandom可能会有点慢，所以建议您使用它作为不同随机数生成器的种子。

如果您的系统没有/dev/urandom，但是有一个/dev/random或类似的文件，那么您可以简单地将传递的路径更改为在urandom_init中打开。urandom_init和urandom中使用的调用和api(我相信)是POSIX兼容的，因此，即使不是所有POSIX兼容的系统，也应该在大多数系统上工作。

注意:如果可用熵不足，从/dev/urandom读取将不会阻塞，因此在这种情况下生成的值可能是密码不安全的。如果您担心这一点，那么使用/dev/random，如果熵不足，它总是会阻塞。

如果您在另一个系统(即。Windows)，然后使用rand或一些内部Windows特定平台依赖的不可移植API。

urandom, rand或arc4random调用的包装器函数:

#define RAND_IMPL /* urandom(see large code block) | rand | arc4random */

int myRandom(int bottom, int top){
    return (RAND_IMPL() % (top - bottom)) + bottom;
}

我们来看看这个。首先，我们使用srand()函数来为随机化器播种。基本上，计算机可以根据输入给srand()的数字生成随机数。如果你给出相同的种子值，那么每次都会生成相同的随机数。

因此，我们必须用一个总是在变化的值来给随机化器播种。我们通过time()函数将当前时间的值提供给它来实现这一点。

现在，当我们调用rand()时，每次都会产生一个新的随机数。

    #include <stdio.h>

    int random_number(int min_num, int max_num);

    int main(void)
    {
        printf("Min : 1 Max : 40 %d\n", random_number(1,40));
        printf("Min : 100 Max : 1000 %d\n",random_number(100,1000));
        return 0;
    }

    int random_number(int min_num, int max_num)
    {
        int result = 0, low_num = 0, hi_num = 0;

        if (min_num < max_num)
        {
            low_num = min_num;
            hi_num = max_num + 1; // include max_num in output
        } else {
            low_num = max_num + 1; // include max_num in output
            hi_num = min_num;
        }

        srand(time(NULL));
        result = (rand() % (hi_num - low_num)) + low_num;
        return result;
    }

如果您需要128个安全随机位，符合RFC 1750的解决方案是读取已知可以生成可用熵位的硬件源(例如旋转磁盘)。更好的是，好的实现应该使用混合函数组合多个源，并最终通过重新映射或删除输出来消除输出分布的倾斜。

如果你需要更多的比特，你需要做的就是从128个安全随机比特的序列开始，并将其拉伸到所需的长度，将其映射到人类可读的文本等等。

如果你想在C中生成一个安全的随机数，我将遵循这里的源代码:

https://wiki.sei.cmu.edu/confluence/display/c/MSC30-C.+Do+not+use+the+rand%28%29+function+for+generating+pseudorandom+numbers

注意，对于Windows bbcryptgenrandom是使用的，而不是CryptGenRandom，在过去的20年里已经变得不安全。您可以亲自确认BCryptGenRandom符合RFC 1750。

For POSIX-compliant operating systems, e.g. Ubuntu (a flavor of Linux), you can simply read from /dev/urandom or /dev/random, which is a file-like interface to a device that generates bits of entropy by combining multiple sources in an RFC 1750 compliant fashion. You can read a desired number of bytes from these "files" with read or fread just like you would any other file, but note that reads from /dev/random will block until a enough new bits of entropy are available, whereas /dev/urandom will not, which can be a security issue. You can get around that by checking the size of the available entropy pool, either my reading from entropy_avail, or by using ioctl.

你也可以使用mathgl库#include <mgl2/mgl_cf.h>(虽然首先你需要安装它，我自己通过MSYS2安装)函数mgl_rnd()。它也有均匀分布，高斯分布等等。这是ez的用法。但我不知道它的特点。