我不知道这在密码学上听起来如何，但它比迄今为止(在我看来)更复杂的解决方案更具可读性和简练性，而且它应该比系统更“随机”。Random-based解决方案。

return alphabet
    .OrderBy(c => Guid.NewGuid())
    .Take(strLength)
    .Aggregate(
        new StringBuilder(),
        (builder, c) => builder.Append(c))
    .ToString();

我不知道我认为这个版本还是下一个版本“更漂亮”，但它们给出了完全相同的结果:

return new string(alphabet
    .OrderBy(o => Guid.NewGuid())
    .Take(strLength)
    .ToArray());

当然，它并没有针对速度进行优化，所以如果每秒生成数百万个随机字符串是关键任务，请尝试另一个!

注意:此解决方案不允许字母中符号的重复，并且字母必须等于或大于输出字符串的大小，使得这种方法在某些情况下不太可取，这完全取决于您的用例。

更新。net 6。RNGCryptoServiceProvider被标记为obsolete。相反，调用RandomNumberGenerator.Create()。答案中的代码已相应更新。

根据评论更新。原始实现生成a-h的时间为1.95%，其余字符的时间为1.56%。更新生成所有字符~1.61%的时间。 FRAMEWORK支持- . net Core 3(以及未来支持. net Standard 2.1或以上版本的平台)提供了一个加密的方法RandomNumberGenerator.GetInt32()，在期望的范围内生成一个随机整数。

与目前提出的一些替代方案不同，这个方案在密码学上是合理的。

using System;
using System.Security.Cryptography;
using System.Text;

namespace UniqueKey
{
    public class KeyGenerator
    {
        internal static readonly char[] chars =
            "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890".ToCharArray(); 

        public static string GetUniqueKey(int size)
        {            
            byte[] data = new byte[4*size];
            using (var crypto = RandomNumberGenerator.Create())
            {
                crypto.GetBytes(data);
            }
            StringBuilder result = new StringBuilder(size);
            for (int i = 0; i < size; i++)
            {
                var rnd = BitConverter.ToUInt32(data, i * 4);
                var idx = rnd % chars.Length;

                result.Append(chars[idx]);
            }

            return result.ToString();
        }

        public static string GetUniqueKeyOriginal_BIASED(int size)
        {
            char[] chars =
                "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890".ToCharArray();
            byte[] data = new byte[size];
            using (RNGCryptoServiceProvider crypto = new RNGCryptoServiceProvider())
            {
                crypto.GetBytes(data);
            }
            StringBuilder result = new StringBuilder(size);
            foreach (byte b in data)
            {
                result.Append(chars[b % (chars.Length)]);
            }
            return result.ToString();
        }
    }
}

基于这里对替代方案的讨论，并根据下面的评论进行了更新/修改。

下面是一个小型测试工具，演示了旧输出和更新输出中的字符分布。关于随机性分析的深入讨论，请访问random.org。

using System;
using System.Collections.Generic;
using System.Linq;
using UniqueKey;

namespace CryptoRNGDemo
{
    class Program
    {

        const int REPETITIONS = 1000000;
        const int KEY_SIZE = 32;

        static void Main(string[] args)
        {
            Console.WriteLine("Original BIASED implementation");
            PerformTest(REPETITIONS, KEY_SIZE, KeyGenerator.GetUniqueKeyOriginal_BIASED);

            Console.WriteLine("Updated implementation");
            PerformTest(REPETITIONS, KEY_SIZE, KeyGenerator.GetUniqueKey);
            Console.ReadKey();
        }

        static void PerformTest(int repetitions, int keySize, Func<int, string> generator)
        {
            Dictionary<char, int> counts = new Dictionary<char, int>();
            foreach (var ch in UniqueKey.KeyGenerator.chars) counts.Add(ch, 0);

            for (int i = 0; i < REPETITIONS; i++)
            {
                var key = generator(KEY_SIZE); 
                foreach (var ch in key) counts[ch]++;
            }

            int totalChars = counts.Values.Sum();
            foreach (var ch in UniqueKey.KeyGenerator.chars)
            {
                Console.WriteLine($"{ch}: {(100.0 * counts[ch] / totalChars).ToString("#.000")}%");
            }
        }
    }
}

更新7/25/2022

根据评论中的一个问题，我很好奇这种分布是否真的是随机的。

我不是统计学家，但我可以在电视上扮演一个。如果一位真正的统计学家愿意插话，那将是最受欢迎的。

有62个可能的输出值(A-Za-Z0-9)和int。用于选择数组索引的最大值。int。MaxValue % 62是1，所以一个字符被选中的概率是其他字符的十亿分之一。我们可以通过在索引之前随机旋转输出值数组来进一步减少选择偏差。

t检验或其他统计度量将是确定输出结果中是否存在偏差的最佳方法，但这不是我在午休时间可以完成的工作，因此我留给您对上述代码的修改，以度量与预期的偏差。注意，它趋于零。

using System.Security.Cryptography;
using System.Text;

const int REPETITIONS = 1_000_000;
const int KEY_SIZE = 32;
int TASK_COUNT = Environment.ProcessorCount - 1;

var expectedPercentage = 100.0 / KeyGenerator.chars.Length;

var done = false;
var iterationNr = 1;
var totalRandomSymbols = 0L;

var grandTotalCounts = new Dictionary<char, long>();
foreach (var ch in KeyGenerator.chars) grandTotalCounts.Add(ch, 0);

while (!done)
{
    var experiments = Enumerable.Range(0, TASK_COUNT).Select(i => Task.Run(Experiment)).ToArray();
    Task.WaitAll(experiments);
    var totalCountsThisRun = experiments.SelectMany(e => e.Result)
        .GroupBy(e => e.Key)
        .Select(e => new { e.Key, Count = e.Select(_ => _.Value).Sum() })
        .ToDictionary(e => e.Key, e => e.Count);

    foreach (var ch in KeyGenerator.chars)
        grandTotalCounts[ch] += totalCountsThisRun[ch];

    var totalChars = grandTotalCounts.Values.Sum();
    totalRandomSymbols += totalChars;

    var distributionScores = KeyGenerator.chars.Select(ch =>
    new
    {
        Symbol = ch,
        OverUnder = (100.0 * grandTotalCounts[ch] / totalChars) - expectedPercentage

    });

    Console.WriteLine($"Iteration {iterationNr++}. Total random symbols: {totalRandomSymbols:N0}");
    foreach (var chWithValue in distributionScores.OrderByDescending(c => c.OverUnder))
    {
        Console.WriteLine($"{chWithValue.Symbol}: {chWithValue.OverUnder:#.00000}%");
    }

    done = Console.KeyAvailable;        
}

Dictionary<char, long> Experiment()
{
    var counts = new Dictionary<char, long>();
    foreach (var ch in KeyGenerator.chars) counts.Add(ch, 0);

    for (int i = 0; i < REPETITIONS; i++)
    {
        var key = KeyGenerator.GetUniqueKey(KEY_SIZE);
        foreach (var ch in key) counts[ch]++;
    }

    return counts;
}

public class KeyGenerator
{
    internal static readonly char[] chars =
        "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ1234567890".ToCharArray();

    public static string GetUniqueKey(int size)
    {
        byte[] data = new byte[4 * size];
        using (var crypto = RandomNumberGenerator.Create())
        {
            crypto.GetBytes(data);
        }
        StringBuilder result = new StringBuilder(size);
        for (int i = 0; i < size; i++)
        {
            var rnd = BitConverter.ToUInt32(data, i * 4);
            var idx = rnd % chars.Length;

            result.Append(chars[idx]);
        }

        return result.ToString();
    }
}

这是我从Dot Net Perls的Sam Allen那里偷来的一个例子

如果你只需要8个字符，那么在系统中使用Path.GetRandomFileName()。IO命名空间。Sam说使用“Path.”这里的GetRandomFileName方法有时更优越，因为它使用RNGCryptoServiceProvider来获得更好的随机性。然而，它被限制为11个随机字符。”

GetRandomFileName总是返回一个12个字符的字符串，第9个字符是句点。所以你需要去掉句点(因为这不是随机的)，然后从字符串中取出8个字符。实际上，你可以只取前8个字符而不用考虑句点。

public string Get8CharacterRandomString()
{
    string path = Path.GetRandomFileName();
    path = path.Replace(".", ""); // Remove period.
    return path.Substring(0, 8);  // Return 8 character string
}

PS:谢谢，Sam

尝试将两部分结合起来:独特(序列、计数器或日期)和随机

public class RandomStringGenerator
{
    public static string Gen()
    {
        return ConvertToBase(DateTime.UtcNow.ToFileTimeUtc()) + GenRandomStrings(5); //keep length fixed at least of one part
    }

    private static string GenRandomStrings(int strLen)
    {
        var result = string.Empty;

        using (var gen = new RNGCryptoServiceProvider())
        {
            var data = new byte[1];

            while (result.Length < strLen)
            {
                gen.GetNonZeroBytes(data);
                int code = data[0];
                if (code > 48 && code < 57 || // 0-9
                    code > 65 && code < 90 || // A-Z
                    code > 97 && code < 122   // a-z
                )
                {
                    result += Convert.ToChar(code);
                }
            }

            return result;
        }
    }

    private static string ConvertToBase(long num, int nbase = 36)
    {
        const string chars = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"; //if you wish to make the algorithm more secure - change order of letter here

        // check if we can convert to another base
        if (nbase < 2 || nbase > chars.Length)
            return null;

        int r;
        var newNumber = string.Empty;

        // in r we have the offset of the char that was converted to the new base
        while (num >= nbase)
        {
            r = (int)(num % nbase);
            newNumber = chars[r] + newNumber;
            num = num / nbase;
        }
        // the last number to convert
        newNumber = chars[(int)num] + newNumber;

        return newNumber;
    }
}

测试:

    [Test]
    public void Generator_Should_BeUnigue1()
    {
        //Given
        var loop = Enumerable.Range(0, 1000);
        //When
        var str = loop.Select(x=> RandomStringGenerator.Gen());
        //Then
        var distinct = str.Distinct();
        Assert.AreEqual(loop.Count(),distinct.Count()); // Or Assert.IsTrue(distinct.Count() < 0.95 * loop.Count())
    }

这里有一个机制来生成一个随机的字母-数字字符串(我用它来生成密码和测试数据)，而不定义字母和数字，

CleanupBase64将删除字符串中必要的部分，并继续递归地添加随机的字母-数字字母。

        public static string GenerateRandomString(int length)
        {
            var numArray = new byte[length];
            new RNGCryptoServiceProvider().GetBytes(numArray);
            return CleanUpBase64String(Convert.ToBase64String(numArray), length);
        }

        private static string CleanUpBase64String(string input, int maxLength)
        {
            input = input.Replace("-", "");
            input = input.Replace("=", "");
            input = input.Replace("/", "");
            input = input.Replace("+", "");
            input = input.Replace(" ", "");
            while (input.Length < maxLength)
                input = input + GenerateRandomString(maxLength);
            return input.Length <= maxLength ?
                input.ToUpper() : //In my case I want capital letters
                input.ToUpper().Substring(0, maxLength);
        }

I was looking for a more specific answer, where I want to control the format of the random string and came across this post. For example: license plates (of cars) have a specific format (per country) and I wanted to created random license plates. I decided to write my own extension method of Random for this. (this is in order to reuse the same Random object, as you could have doubles in multi-threading scenarios). I created a gist (https://gist.github.com/SamVanhoutte/808845ca78b9c041e928), but will also copy the extension class here:

void Main()
{
    Random rnd = new Random();
    rnd.GetString("1-###-000").Dump();
}

public static class RandomExtensions
{
    public static string GetString(this Random random, string format)
    {
        // Based on http://stackoverflow.com/questions/1344221/how-can-i-generate-random-alphanumeric-strings-in-c
        // Added logic to specify the format of the random string (# will be random string, 0 will be random numeric, other characters remain)
        StringBuilder result = new StringBuilder();
        for(int formatIndex = 0; formatIndex < format.Length ; formatIndex++)
        {
            switch(format.ToUpper()[formatIndex])
            {
                case '0': result.Append(getRandomNumeric(random)); break;
                case '#': result.Append(getRandomCharacter(random)); break;
                default : result.Append(format[formatIndex]); break;
            }
        }
        return result.ToString();
    }

    private static char getRandomCharacter(Random random)
    {
        string chars = "ABCDEFGHIJKLMNOPQRSTUVWXYZ";
        return chars[random.Next(chars.Length)];
    }

    private static char getRandomNumeric(Random random)
    {
        string nums = "0123456789";
        return nums[random.Next(nums.Length)];
    }
}