In cryptography, the Advanced Encryption Standard (AES), also known as Rijndael, is a block cipher adopted as an encryption standard by the us government, and is expected to be used worldwide and analysed extensively, as was the case with its predecessor, the Data encryption standard(DES). It was adopted by National institute of standard and technology(NIST) as US FIPS PUB 197 in November2001 after a 5-year standardisation process The cipher was developed by two Belgian cryptographers, Joan Daeman andVincent Rijamean, and submitted to the AES selection process under the name "Rijndael", a Portmanteau comprised of the names of the inventors. Rijndael can be pronounced "Rhine dahl", a long "i" and a silent "e" (IPA: [aindal]). In the sound file linked below, it is pronounced aindau]. AES is intended to be a stronger, more efficient successor to Triple Data Encryption Standard (3DES), which replaced the aging DES, which was cracked in less than three days in July 1998. "Until we have the AES, 3DES will still offer protection for years to come. So there is no need to immediately switch over," says Edward Roback, acting chief of the computer security division at NIST and chairman of the AES selection committee. "What AES will offer is a more efficient algorithm. . . . It will be a federal standard, but it will be widely implemented in the IT community." According to Roback, efficiency of the proposed algorithms is measured by how fast they can encrypt and decrypt information, how fast they can present an encryption key and how much information they can encrypt. "There are actually maximum thresholds that you can get if you have high data feeds, (and) 3DES can't accommodate them," says Roback. The AES review committee is also looking at how much space the algorithm takes up on a chip and how much memory it requires. Roback says the selection of a more efficient AES will also result in cost savings and better use of resources. "DES was designed for hardware implementations, and we are now living in a world of much more efficient software, and we have learned an awful lot about the design of algorithms," says Roback. "When you start multiplying this with the billions of implementations done daily, the saving on overhead on the networks will be enormous."