In this paper we attempt to determine the effectiveness of using entropy, as defined in NIST SP800-63, as a measurement of the security provided by various password creation policies. This is accomplished by modeling the success rate of current password cracking techniques against real user passwords. These data sets were collected from several different websites, the largest one containing over 32 million passwords. This focus on actual attack methodologies and real user passwords quite possibly makes this one of the largest studies on password security to date. In addition we examine what these results mean for standard password creation policies, such as minimum password length, and character set requirements.

Numerous techniques have been proposed by which an end-system, subjected to a denial-of-service flood, filters the offending traffic. In this paper, we provide an empirical analysis of several such proposals, using traffic recorded at the border of a large network and including real DoS traffic. We focus our analysis on four filtering techniques, two based on the addresses from which the victim server typically receives traffic (static clustering and network-aware clustering), and two based on coarse indications of the path each packet traverses (hop-count filtering and path identifiers). Our analysis reveals challenges facing the proposed techniques in practice, and the implications of these issues for effective filtering. In addition, we compare techniques on equal footing, by evaluating the performance of one scheme under assumptions made by another. We conclude with an interpretation of the results and suggestions for further analysis.