Results 1  10
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19
Managing Attack Graph Complexity through Visual Hierarchical Aggregation
 In VizSEC/DMSEC ’04: Proceedings of the 2004 ACM workshop on Visualization and
, 2004
"... We describe a framework for managing network attack graph complexity through interactive visualization, which includes hierarchical aggregation of graph elements. Aggregation collapses nonoverlapping subgraphs of the attack graph to single graph vertices, providing compression of attack graph compl ..."
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Cited by 39 (4 self)
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We describe a framework for managing network attack graph complexity through interactive visualization, which includes hierarchical aggregation of graph elements. Aggregation collapses nonoverlapping subgraphs of the attack graph to single graph vertices, providing compression of attack graph complexity. Our aggregation is recursive (nested), according to a predefined aggregation hierarchy. This hierarchy establishes rules at each level of aggregation, with the rules being based on either common attribute values of attack graph elements or attack graph connectedness. The higher levels of the aggregation hierarchy correspond to higher levels of abstraction, providing progressively summarized visual overviews of the attack graph. We describe rich visual representations that capture relationships among our semanticallyrelevant attack graph abstractions, and our views
On External Memory MST, SSSP and Multiway Planar Graph Separation (Extended Abstract)
, 2000
"... Recently external memory graph algorithms have received considerable attention because massive graphs arise naturally in many applications involving massive data sets. Even though a large number of I/Oefficient graph algorithms have been developed, a number of fundamental problems still remain ..."
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Cited by 33 (11 self)
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Recently external memory graph algorithms have received considerable attention because massive graphs arise naturally in many applications involving massive data sets. Even though a large number of I/Oefficient graph algorithms have been developed, a number of fundamental problems still remain open. In this paper we develop improved algorithms for the problem of computing a minimum spanning tree of a general graph G = (V; E), as well as new algorithms for the single source shortest paths and the multiway graph separation problems on planar graphs.
On externalmemory MST, SSSP and multiway planar graph separation
 In Proc. 8th Scandinavian Workshop on Algorithmic Theory, volume 1851 of LNCS
, 2000
"... Recently external memory graph algorithms have received considerable attention because massive graphs arise naturally in many applications involving massive data sets. Even though a large number of I/Oefficient graph algorithms have been developed, a number of fundamental problems still remain open ..."
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Cited by 24 (2 self)
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Recently external memory graph algorithms have received considerable attention because massive graphs arise naturally in many applications involving massive data sets. Even though a large number of I/Oefficient graph algorithms have been developed, a number of fundamental problems still remain open. In this paper we develop an improved algorithm for the problem of computing a minimum spanning tree of a general graph, as well as new algorithms for the single source shortest paths and the multiway graph separation problems on planar graphs.
On ExternalMemory Planar Depth First Search
 Journal of Graph Algorithms and Applications
"... Even though a large number of I/Oefficient graph algorithms have been developed, a number of fundamental problems still remain open. For example, no space and I/Oefficient algorithms are known for depthfirst search or breadthfirst search in sparse graphs. In this paper we present two new re ..."
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Cited by 24 (15 self)
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Even though a large number of I/Oefficient graph algorithms have been developed, a number of fundamental problems still remain open. For example, no space and I/Oefficient algorithms are known for depthfirst search or breadthfirst search in sparse graphs. In this paper we present two new results on I/Oefficient depthfirst search in an important class of sparse graphs, namely undirected embedded planar graphs. We develop a new efficient depthfirst search algorithm and show how planar depthfirst search in general can be reduced to planar breadthfirst search. As part of the first result we develop the first I/Oefficient algorithm for finding a simple cycle separator of a biconnected planar graph. Together with other recent reducibility results, the second result provides further evidence that external memory breadthfirst search is among the hardest problems on planar graphs. 1
Range searching over tree cross products
 In Proc. 8th European Symposium on Algorithms (ESA
, 2000
"... Abstract. We introduce the tree crossproduct problem, which abstracts a data structure common to applications in graph visualization, string matching, and software analysis. We design solutions with a variety of tradeoffs, yielding improvements and new results for these applications. 1 ..."
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Cited by 19 (0 self)
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Abstract. We introduce the tree crossproduct problem, which abstracts a data structure common to applications in graph visualization, string matching, and software analysis. We design solutions with a variety of tradeoffs, yielding improvements and new results for these applications. 1
Keyword Search on External Memory Data Graphs
, 2008
"... Keyword search on graph structured data has attracted a lot of attention in recent years. Graphs are a natural “lowest common denominator” representation which can combine relational, XML and HTML data. Responses to keyword queries are usually modeled as trees that connect nodes matching the keyword ..."
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Cited by 19 (1 self)
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Keyword search on graph structured data has attracted a lot of attention in recent years. Graphs are a natural “lowest common denominator” representation which can combine relational, XML and HTML data. Responses to keyword queries are usually modeled as trees that connect nodes matching the keywords. In this paper we address the problem of keyword search on graphs that may be significantly larger than memory. We propose a graph representation technique that combines a condensed version of the graph (the “supernode graph”) which is always memory resident, along with whatever parts of the detailed graph are in a cache, to form a multigranular graph representation. We propose two alternative approaches which extend existing search algorithms to exploit multigranular graphs; both approaches attempt to minimize IO by directing search towards areas of the graph that are likely to give good results. We compare our algorithms with a virtual memory approach on several real data sets. Our experimental results show significant benefits in terms of reduction in IO due to our algorithms.
Visualizing large graphs with compoundfisheye views and treemaps
 In 12th Symposium on Graph Drawing (GD
, 2004
"... Abstract. Compoundfisheye views are introduced as a method for the display and interaction with large graphs. The method relies on a hierarchical clustering of the graph, and a generalization of the traditional fisheye view, together with a treemap representation of the cluster tree. 1 ..."
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Cited by 10 (1 self)
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Abstract. Compoundfisheye views are introduced as a method for the display and interaction with large graphs. The method relies on a hierarchical clustering of the graph, and a generalization of the traditional fisheye view, together with a treemap representation of the cluster tree. 1
HGV: A Library for Hierarchies, Graphs, and Views
 American Chemical Society
, 2002
"... We introduce the base architecture of a software library which combines graphs, hierarchies, and views and describes the interactions between them. Each graph may have arbitrarily many hierarchies and each hierarchy may have arbitrarily many views. Both the hierarchies and the views can be added ..."
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Cited by 5 (3 self)
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We introduce the base architecture of a software library which combines graphs, hierarchies, and views and describes the interactions between them. Each graph may have arbitrarily many hierarchies and each hierarchy may have arbitrarily many views. Both the hierarchies and the views can be added and removed dynamically from the corresponding graph and hierarchy, respectively. The software library shall serve as a platform for algorithms and data structures on hierarchically structured graphs. Such graphs become increasingly important and occur in special applications, e. g., call graphs in software engineering or biochemical pathways, with a particular need to manipulate and draw graphs.
Evolutionary and Collaborative Software Architecture Recovery with Softwarenaut
"... Architecture recovery is an activity applied to a system whose initial architecture has eroded. When the system is large, the user must use dedicated tools to support the recovery process. We present Softwarenaut – a tool which supports architecture recovery through interactive exploration and visua ..."
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Cited by 5 (4 self)
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Architecture recovery is an activity applied to a system whose initial architecture has eroded. When the system is large, the user must use dedicated tools to support the recovery process. We present Softwarenaut – a tool which supports architecture recovery through interactive exploration and visualization. Classical architecture recovery features, such as filtering and details on demand, are enhanced with evolutionary capabilities when multiversion information about a subject system is available. The tool allows sharing and discovering the results of previous analysis sessions through a global repository of architectural views indexed by systems. We present the features of the tool together with the architecture recovery process that it supports using as a casestudy ArgoUML, a wellknown open source Java system.
I/OEfficient Planar Separators and Applications
, 2001
"... We present a new algorithm to compute a subset S of vertices of a planar graph G whose removal partitions G into O(N/h) subgraphs of size O(h) and with boundary size O( p h) each. The size of S is O(N= p h). Computing S takes O(sort(N)) I/Os and linear space, provided that M 56hlog² B. Together with ..."
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Cited by 3 (1 self)
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We present a new algorithm to compute a subset S of vertices of a planar graph G whose removal partitions G into O(N/h) subgraphs of size O(h) and with boundary size O( p h) each. The size of S is O(N= p h). Computing S takes O(sort(N)) I/Os and linear space, provided that M 56hlog² B. Together with recent reducibility results, this leads to O(sort(N)) I/O algorithms for breadthfirst search (BFS), depthfirst search (DFS), and single source shortest paths (SSSP) on undirected embedded planar graphs. Our separator algorithm does not need a BFS tree or an embedding of G to be given as part of the input. Instead we argue that "local embeddings" of subgraphs of G are enough.