Online Program
Saturday, February 20  
PS3 Poster Session 3 & Continental Breakfast sponsored by Capital One 
Sat, Feb 20, 8:00 AM  9:15 AM
Ballroom Foyer 
Use of Hamming Weights Instead of Uniform Distributions to Analyze a Set of Strings for Randomness (303256)Gavin Minh Pham, Southern Methodist University Darwin Deason Institute for Cyber Security*Josh Rendon, Southern Methodist University Darwin Deason Institute for Cyber Security Micah Thornton, Southern Methodist University Darwin Deason Institute for Cyber Security Mitch Thornton, Southern Methodist University Darwin Deason Institute for Cyber Security Keywords: hamming weight, bit string, randomness, big data statistic, security, computer security There are a number of reasons why one may desire to have a random string, including, but not limited to: sources of entropy in a system, good cryptographic codes, statistical modeling of a random distribution. Historically when studying if a bit string is random, one would model that string as a uniform distribution with equal probability of each bit being one or zero. While this method works well for a single bit string, we have identified that for an ensemble of bit strings produced by a single generator function, the Hamming Weight (HW) of the bit strings can be a more effective statistic. Using properties of a bit string, with each bit position being limited to a one or a zero, for any bit string of Nbits its HW will be restricted to the range [0,2^N1]. Likewise a histogram of its Hamming Weights binned from HW = 0 to HW =2^N1 will follow a binomial distribution with probability p = ½. In this work we present a method for reasoning about ensembles of bit strings for randomness using the Hamming Weight histogram of the bit strings.
