Drawing random idea generator

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Drawing random idea generator

By ExtremeTech Staff on May 18, 2001 at 12:00 am This site may earn affiliate commissions from the links on this page. Terms of use. This analysis for Fortran's random-number generator presents several ways to analyze the true randomness of the function. Computers generate random number for everything from cryptography to video games and gambling. There are two categories of random numbers -- "true" random numbers and pseudorandom numbers -- and the difference is important for the security of encryption systems. Computers can generate truly random numbers by observing some outside data, like mouse movements or fan noise, which is not predictable, and creating data from it. This is known as entropy. Other times, they generate "pseudorandom" numbers by using an algorithm so the results appear random, even though they aren't. This topic has become more controversial recently, with many people questioning whether Intel's built-in hardware random number generator chip is trustworthy. To understand why it might not be trustworthy, you'll have to understand how random numbers are generated in the first place, and what they're used for. What Random Numbers Are Used For Random numbers have been used for many thousands of years. Whether it's flipping a coin or rolling a dice, the goal is to leave the end result up to random chance. Random number generators in a computer are similar -- they're an attempt to achieve an unpredictable, random result. RELATED: What Is Encryption, and How Does It Work? Random number generators are useful for many different purposes. Aside from obvious applications like generating random numbers for the purposes of gambling or creating unpredictable results in a computer game, randomness is important for cryptography. Cryptography requires numbers that attackers can't guess. We can't just use the same numbers over and over. We want to generate these numbers in a very unpredictable way so attackers can't guess them. These random numbers are essential for secure encryption, whether you're encrypting your own files or just using an HTTPS website on the Internet. True Random Numbers You may be wondering how a computer can actually generate a random number. Where does this "randomness" come from. If it's just a piece of computer code, isn't it possible the numbers the computer generates could be predictable? We generally group the random numbers computers generate into two types, depending on how they're generated: "True" random numbers and pseudorandom numbers. To generate a "true" random number, the computer measures some type of physical phenomenon that takes place outside of the computer. For example, the computer could measure the radioactive decay of an atom. According to quantum theory, there's no way to know for sure when radioactive decay will occur, so this is essentially "pure randomness" from the universe. An attacker wouldn't be able to predict when radioactive decay would occur, so they wouldn't know the random value. For a more day-to-day example, the computer could rely on atmospheric noise or simply use the exact time you press keys on your keyboard as a source of unpredictable data, or entropy. For example, your computer might notice that you pressed a key at exactly 0.23423523 seconds after 2 p.m.. Grab enough of the specific times associated with these key presses and you'll have a source of entropy you can use to generate a "true" random number. You're not a predictable machine, so an attacker can't guess the precise moment when you press these keys. The /dev/random device on Linux, which generates random numbers, "blocks" and doesn't return a result until it gathers enough entropy to return a truly random number. Pseudorandom Numbers Pseudorandom numbers are an alternative to "true" random numbers. A computer could use a seed value and an algorithm to generate numbers that appear to be random, but that are in fact predictable. The computer doesn't gather any random data from the environment. This isn't necessarily a bad thing in every situation. For example, if you're playing a video game, it doesn't really matter whether the events that occur in that game are caused by "true" random numbers or pseudorandom numbers. On the other hand, if you're using encryption, you don't want to use pseudorandom numbers that an attacker could guess. For example, let's say an attacker knows the algorithm and seed value a pseudorandom number generator uses. And let's say an encryption algorithm gets a pseudorandom number from this algorithm and uses it to generate an encryption key without adding any additional randomness. If an attacker knows enough, they could work backwards and determine the pseudorandom number the encryption algorithm must have chosen in that case, breaking the encryption. The NSA and Intel's Hardware Random Number Generator To make things easier for developers and help generate secure random numbers, Intel chips include a hardware-based random number generator known as RdRand. This chip uses an entropy source on the processor and provides random numbers to software when the software requests them. The problem here is that the random number generator is essentially a black box and we don't know what's going on inside it. If RdRand contained an NSA backdoor, the government would be able to break encryption keys that were generated with only data supplied by that random number generator. This is a serious concern. In December 2013, FreeBSD's developers removed support for using RdRand directly as a source of randomness, saying they couldn't trust it. [Source] The output of the RdRand device would be fed into another algorithm that adds additional entropy, ensuring that any backdoors in the random number generator wouldn't matter. Linux already worked in this way, further randomizing the random data coming from RdRand so that it wouldn't be predictable even if there was a backdoor. [Source] In a recent AMA ("Ask Me Anything") on Reddit, Intel CEO Brian Krzanich did not answer questions about these concerns. [Source] Of course, this likely isn't just a problem with Intel chips. FreeBSD's developers called out Via's chips by name, too. This controversy shows why generating random numbers that are truly random and aren't predictable is so important. To generate "true" random numbers, random number generators gather "entropy," or seemingly random data from the physical world around them. For random numbers that don't really need to be random, they may just use an algorithm and a seed value. Image Credit: rekre89 on Flickr, Lisa Brewster on Flickr, Ryan Somma on Flickr, huangjiahui on Flickr Sometimes, you might need some boilerplate or filler text in a Word document. One solution is to head over to a lorem ipsum or dummy text generator to create that text. Alternatively, you can create the text yourself directly in Word. Generate Random Text with the Rand Formula If you want to use random (yet coherent) text as filler content in your Word document, you can use the random content generation formula provided by Word. There are, however, a few notes to make when using this function, depending on how much text you need. The first method is to simply type in the following formula: =Rand() This will automatically generate five paragraphs, each containing three sentences. You can change how much random text Word generates by filling in what's between the parentheses. To do that, you'll use =Rand(x,y), where x is the number of paragraphs and y is the number of sentences in each paragraph. For example, if you want seven paragraphs that each contain four sentences, you'd use the following formula: =Rand(7,4) There is a maximum amount you can input at once, though. However, you can just reuse the same formula as many times as necessary. Generate Lorem Ipsum Text with the Lorem Formula If you're feeling a bit more old school, Word can also generate Lorem Ipsum text in the same way. And even if it's not the tradition you're after, Lorem Ipsum text has its place. When you use readable English text (like that generated by the rand formula), it can be a distraction if what you want people looking at is the design of a document. The same rules apply here as the previous method. Type in =Lorem() and then hit Enter, and Word will create five paragraphs of Lorem Ipsum text, each containing three sentences. You can modify the amount of text the same way as with the rand formula, too. If you want four paragraphs that each contain nine sentences, you would type the following formula and then hit Enter: =Lorem(4,9) Be mindful that, when using this method, the sentences tend to be much shorter. That said, you may consider increasing the amount entered in the y coordinate. Generate "Quick Brown Fox" Text with the Old Rand Formula "The quick brown fox jumps over the lazy dog." Sound familiar? Back in the day, if you used the rand formula, Word would generate this infamous pangram. However, this was replaced with the current text generation when Office 2007 rolled out. It wasn't discontinued, though, so if you want to generate this holoalphabetic sentence, type in the following formula and hit Enter: =rand.old() The default for this method is three paragraphs that each contain three sentences. As with the other methods, though, you can fill those parentheses to get more precision. For example, =rand.old(5,5) would generate five paragraphs that each repeat that sentence five times. Instructables is a community for people who like to make things. Come explore, share, and make your next project with us!Instructables is a community for people who like to make things. Come explore, share, and make your next project with us!Instructables is a community for people who like to make things. Come explore, share, and make your next project with us!Instructables is a community for people who like to make things. Come explore, share, and make your next project with us!Instructables is a community for people who like to make things. Come explore, share, and make your next project with us!Instructables is a community for people who like to make things. 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