Producing approximate answers to database queries

We have designed and implemented a query processor, called APPROXIMATE, that makes approximate answers available if part of the database is unavailable or if there is not enough time to produce an exact answer. The accuracy of the approximate answers produced improves monotonically with the amount of data retrieved to produce the result. The exact answer is produced if all of the needed data are available and query processing is allowed to continue until completion. The monotone query processing algorithm of APPROXIMATE works within the standard relational algebra framework and can be implemented on a relational database system with little change to the relational architecture. We describe here the approximation semantics of APPROXIMATE that serves as the basis for meaningful approximations of both set-valued and single-valued queries. We show how APPROXIMATE is implemented to make effective use of semantic information, provided by an object-oriented view of the database, and describe the additional overhead required by APPROXIMATE

Secret Little Functions and Codebook for Protecting Users from Password Theft

Abstract—In this paper, we discuss how to prevent users’ passwords from being stolen by adversaries. We propose differentiated security mechanisms in which a user has the freedom to choose a virtual password scheme ranging from weak security to strong security. The tradeoff is that the stronger the scheme, the more complex the scheme may be. Among the schemes, we have a default method (i.e., traditional password scheme), system recommended function, user-specified function, user-specified program, etc. A function/program is used to implement the virtual password concept with a trade off of security for complexity requiring a small amount of human computing. We further propose codebook approach to serve as system recommended functions and provide a security analysis. For user-specified functions, we adopt secret little functions, in which security is enhanced by hiding secret functions/algorithms. I

Satisfying

temporal consistency constraints of real-time database

Data Modeling in the Cloud

In this paper we describe ERDPlus, a free web-based data modeling tool we developed for use in academic settings. The paper includes a comparison of ERDPlus to forty existing data modeling tools. This comparison shows how ERDPlus differs from existing data-modeling tools, and how it facilitates data modeling education. Unlike the existing tools, ERDPlus is web-based, free for academic use, provides free cloud storage of diagrams, works on both Mac and Windows computers, and is capable of creating models for both operational and analytical databases. This paper also includes the description of the usability survey we undertook to validate that ERDPlus is easy to learn and use for novice students learning about data modeling