数据加密算法(Data Encryption Algorithm,DEA)是一种对称加密算法,很可能是使用最广泛的密钥系统,特别是在保护金融数据的安全中,最初开发的DEA是嵌入硬件中的。通常,自动取款机(Automated Teller Machine,ATM)都使用DEA。它出自IBM的研究工作,IBM也曾对它拥有几年的专利权,但是在1983年已到期后,处于公有范围中,允许在特定条件下可以免除专利使用费而使用。1977年被美国政府正式采纳。 DES的原始思想可以参照二战德国的恩格玛机,其基本思想大致相同。传统的密码加密都是由古代的循环移位思想而来,恩格玛机在这个基础之上进行了扩散模糊。但是本质原理都是一样的。现代DES在二进制级别做着同样的事:替代模糊,增加分析的难度。 DES的加密原理,是使用一个 56 位的密钥以及附加的 8 位奇偶校验位,产生最大 64 位的分组大小。这是一个迭代的分组密码,使用称为 Feistel 的技术,其中将加密的文本块分成两半。使用子密钥对其中一半应用循环功能,然后将输出与另一半进行“异或”运算;接着交换这两半,这一过程会继续下去,但最后一个循环不交换。DES 使用 16 个循环,使用异或,置换,代换,移位操作四种基本运算。 类似于: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当然,这些都是base64编码。那么,什么是base64呢? Base64是网络上最常见的用于传输8Bit字节代码的编码方式之一,大家可以查看RFC2045~RFC2049,上面有MIME的详细规范。Base64编码可用于在HTTP环境下传递较长的标识信息。例如,在Java Persistence系统Hibernate中,就采用了Base64来将一个较长的唯一标识符(一般为128-bit的UUID)编码为一个字符串,用作HTTP表单和HTTP GET URL中的参数。在其他应用程序中,也常常需要把二进制数据编码为适合放在URL(包括隐藏表单域)中的形式。此时,采用Base64编码不仅比较简短,同时也具有不可读性,即所编码的数据不会被人用肉眼所直接看到。 比如,编写一个“123”,得出的结果就是“MTIz”。
原文地址:https://www.cnblogs.com/lovesoul/p/12122278.html