metric key(s) used in the encryption of the actual content has nothing to do with the underlying cryptography. These are usually random or pseudorandom bit sequences that are generated by one of the parties based on random number generation (RNG) techniques. In some systems, a physically separate device generates the random numbers. This poses the danger of physically tampering with the sys- tem, if, for example, someone opens up the chassis and physically injects values into the encryptor chip that replace the intended RNG. The military and intelligence communities require tamper- resistant designs based on strict standards. In these systems, the slightest effort from an intruder to open a system chassis box or to even remotely try to physically access internal circuits will leave indelible traces and marks, and will zeroize internal registers, thereby prohibiting piracy and illicit use. The main processor (or encryption processor) requests a random bit sequence. The RNG then produces it and feeds it to the encryption processor, which can be a CPU running security algorithms in software or a security coprocessor chip. In some other systems, an embedded RNG (many technologies allow this to be done inside a sili- con die) inside the security coprocessor chip generates these random values. The subject of RNG is vast. The references listed at the end of the chapter can provide more information on the subject and its ramifications. We must distinguish between truly random and pseudorandom or quasirandom bit sequences. Several statistical tests correlating samples of larger windows rolling over a bit sequence can deter- mine a series of criteria according to which scientists rate the degree of randomness in bit sequences. The National Institute of Standards and Technology (NIST) web site (www.itl.nist.gov/fipspubs/ index.htm) contains several test suites designed to check and rate the degree of randomness. Just because something looks random does not mean it is actually random. Very successful attacks have been staged