如果随机数搞乱了，那么基于它之上的所有安全都是可疑的。
If random numbers are messed up, all security based on it is suspicious.
回想一下我们上周介绍的非常基本的构建块，它允许您获取1到10或1或100之间的随机数。
Recall that very basic building block we introduced last week which allowed you to grab a random number between 1 and 10 or 1 or a hundred.
使用Boost库生成随机数。
使用Boost随机数生成器。
我专门研究随机数生成过程。
计算机通常只生成伪随机数。
随机数是确保安全性的重要组成部分。
Random Numbers are a key component to making all this security happen.
随后出现一个随机数,然后他们再追问答案
So it comes up with a random number then they asked for the answer.
清单7：用随机数重写。
因而在这个例子中，我将使用这种随机数技术。
Thus, in this example, I shall use this random number technique.
向执行线程分配随机数将帮助您实现这个目的。
Assigning random Numbers to execution threads will help you achieve this.
根据两个随机数计算索赔金额(参见上一节)。
Calculates the claim amount based on two random Numbers (see "Calculating the claim amount" above for more information).
该方法基于迭代评估，利用随机数集作为输入。
The method is based on iterative evaluations using sets of random numbers as inputs.
使用了新的Random类来生成随机数序列。
如何在XML消息中使用随机数作为加密密钥？
How to use a random number as an encryption key in XML messages?
跟随其后是28字节的随机数，它将在后面使用。
It's followed by 28 random bytes. This will be used later on.
就是您的随机数。
其他的增强有设备的随机数生成器以及双精度的支持。
Other enhancements are on-device random number generation and double precision support.
第一个随机数（R1）判定索赔额是否低于 $500。
The first random number (R1) determines if the claim amount is less than $500 or greater than $500.
在针对历史堆栈的测试应用程序中，只存储随机数作为事件。
In the testing application for the history stack, we only stored random Numbers as events.
所以，让我们更进一步，在产生随机数的地方加一个互斥量。
So, let's say we go ahead and add a mutex that surrounds the random number generator.
到了这儿，您就可以回到前面给每个骰子加一个随机数产生器。
Having done this, you could then go ahead and give each die its own random number generator.
第三个参数允许我们覆盖JSSE的随机数生成器(RNG)。
The third parameter would allow us to override JSSE's random number generator (RNG).
蒙特卡洛模拟涉及了使用随机数和概率来找到复杂问题的解决方案。
A Monte Carlo Simulation involves the use of random Numbers and probability to find solutions to complex problems.
在本例中，我们用一些数学函数创建0到100之间的一个随机数。
In this case, you're using some math functions to create a random number from 0 to 100.
如果随机数搞乱了，那么基于它之上的所有安全都是可疑的。
If you mess it up, all the security built on top of it is suspect.
下面，需要生成nonce字段，它包装了一个随机数作为一个整数。
Next, I need to author the nonce field, which wraps a random number as an integer.
然后它会在0,1中取一个随机数，也就是0到1之间包括0但不包括1。
It then picks a random number in 0, 1, that is, in the interval from zero inclusive to one exclusive.
模块现在有一个按钮，它用于从服务器中检索随机数并将其与单击次数相比较。
The module now has a button that retrieves the random number from the server and compares it to your click count.
模块现在有一个按钮，它用于从服务器中检索随机数并将其与单击次数相比较。
The module now has a button that retrieves the random number from the server and compares it to your click count.
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