@article {57,
	title = {Visual Correlation Analysis of Numerical and  Categorical Data on the Correlation Map},
	journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG {\textquoteright}14)},
	year = {2014},
	month = {12/2014},
	abstract = {<p>Correlation analysis can reveal the complex relationships that often exist among the variables in multivariate data.\&nbsp; However, as the number of variables grows, it can be difficult to gain a good understanding of the correlation landscape and\&nbsp; important intricate relationships might be missed. We previously introduced a technique that arranged the variables into a 2D\&nbsp; layout, encoding their pairwise correlations. We then used this layout as a network for the interactive ordering of axes in parallel\&nbsp; coordinate displays. Our current work expresses the layout as a correlation map and employs it for visual correlation analysis. In\&nbsp; contrast to matrix displays where correlations are indicated at intersections of rows and columns, our map conveys correlations\&nbsp; by spatial proximity which is more direct and more focused on the variables in play. We make the following new contributions,\&nbsp; some unique to our map: (1) we devise mechanisms that handle both categorical and numerical variables within a unified\&nbsp; framework, (2) we achieve scalability for large numbers of variables via a multi-scale semantic zooming approach, (3) we\&nbsp; provide interactive techniques for exploring the impact of value bracketing on correlations, and (4) we visualize data relations\&nbsp; within the sub-spaces spanned by correlated variables by projecting the data into a corresponding tessellation of the map.</p>
},
	url = {http://www.fsl.cs.stonybrook.edu/docs/tvcg14/TVCG_Correlation_MinorRev_Final.pdf},
	author = {Zhiyuan Zhang and Kevin T. McDonnell and Erez Zadok and Klaus Mueller}
}
@book {54,
	title = {Verification of Security Policy Enforcement in Enterprise Systems},
	series = {Emerging Challenges for Security, Privacy and Trust },
	number = {297},
	year = {2009},
	pages = {202-213},
	publisher = {Springer Berlin Heidelberg},
	organization = {Springer Berlin Heidelberg},
	edition = {2009},
	abstract = {<p>Many security requirements for enterprise systems can be expressed in a natural way as high-level access control policies. A high-level policy may refer to abstract information resources, independent of where the information is stored; it controls both direct and indirect accesses to the information; it may refer to the context of a request, i.e., the request{\textquoteright}s path through the system; and its enforcement point and enforcement mechanism may be unspecified. Enforcement of a high-level policy may depend on the system architecture and the configurations of a variety of security mechanisms, such as firewalls, host login permissions, file permissions, DBMS access control, and application-specific security mechanisms. This paper presents a framework in which all of these can be conveniently and formally expressed, a method to verify that a high-level policy is enforced, and an algorithm to determine a trusted computing base for each resource.</p>
},
	isbn = {978-3-642-01243-3},
	doi = {10.1007/978-3-642-01244-0_18},
	url = {http://link.springer.com/chapter/10.1007\%2F978-3-642-01244-0_18},
	author = {Puneet Gupta and Scott Stoller}
}
