Network-of-networks (NoN) is a graph-theoretic model of interdependent networks that have distinct dynamics at each network (layer). By adding special edges to represent relationships between nodes in different layers, NoN provides a unified mechanism to study interdependent systems intertwined in a complex relationship. While NoN based models have been proposed for cyber-physical systems, in this position paper we build towards a three-layered NoN model for an enterprise cyber system. Each layer captures a different facet of a cyber system. We present in-depth discussion for four major graph-theoretic applications to demonstrate how the three-layered NoN model can be leveraged for continuous system monitoring and mission assurance. A longer version of this paper can be accessed from arXiv [1].

Within large amounts of seemingly unstructured data it can be diffcult to find signatures of events. In our work we transform unstructured data into a graph representation. By doing this we expose underlying structure in the data and can take advantage of existing graph analytics capabilities, as well as develop new capabilities. Currently we focus on applications in cybersecurity and communication domains. Within cybersecurity we aim to find signatures for perpetrators using the pass-the-hash attack, and in communications we look for emails or phone calls going up or down a chain of command. In both of these areas, and in many others, the signature we look for is a path with certain temporal properties. In this paper we discuss our methodology for finding these temporal paths within large graphs.

This paper introduces a novel graph analytic metric that can be used to measure the potential vulnerability of a cyber network to specific types of attacks that use lateral movement and privilege escalation such as the well-known Pass The Hash, (PTH). The metric is computed from an oriented subgraph of the underlying cyber network induced by selecting only those edges for which a given property holds between the two vertices of the edge. The metric with respect to a select node on the subgraph is defined as the likelihood that the select node is reachable from another arbitrary node in the graph. This metric can be calculated dynamically from the authorization and auditing layers during the network security authorization phase and will potentially enable predictive deterrence against attacks such as PTH.

Summary form only given. A hybrid divide and conquer algorithm is one that switches from a divide and conquer to an iterative strategy at a specified problem size. Such algorithms can provide significant performance improvements relative to alternatives that use a single strategy. However, the identification of the optimal problem size at which to switch for a particular algorithm and platform can be challenging. We describe an automated approach to this problem that first conducts experiments to explore the performance space on a particular platform and then uses the resulting performance data to construct an optimal hybrid algorithm on that platform. We implement this technique in a tool, Ouroboros, that automatically constructs a high-performance hybrid algorithm from a set of registered algorithms. We present results obtained with this tool for several classical divide and conquer algorithms, including matrix multiply and sorting, and report speedups of up to six times achieved over nonhybrid algorithms.

This study presents a technique that can significantly improve the performance of a distributed application by allowing the application to locally adapt to architectural characteristics of distinct resources in a distributed system. Application performance is sensitive to system architecture-application parameter pairings. In a distributed or Grid enabled application, a single parameter configuration for the whole application will not always be optimal for every participating resource. In particular, some configurations can significantly degrade performance. Furthermore, the behavior of a system may change during the course of the run. The technique described here provides an automated mechanism for run-time adaptation of application parameters to the local system architecture. Using a scaled-down simulation of a Monte Carlo physics code, we demonstrate that this technique can conservatively achieve speedups up to 65% on individual resources and may even provide order of magnitude speedup in the extreme case.

We p~esent transposition a~gorithms fo?' matrices that do not fit in main memory.Transposition is interpreted m a permutation of the vector obtained by mapping a matriz to linear memoTy.A lgopithms am derived j%om factorization of this perm~tation, using a class of permutations related to the tensor prodwt.Using this formulation of transposition, we jirst obtain seveTal known aigo?'ithms and then we derive a new algorithm which Teduces the number of dish accesses TequiTed.The new algoTithm was compaTed to ezisting algorithms wing an implementation on the Intel iPSC/860.Thti comparison shows the benefits of the new aigoTithm.

The authors study the use of multilinear algebra in designing and implementing algorithms for linear computations. In particular, they discuss their experience in using these techniques on the Cray Y-MP and to implement Strassen's matrix multiplication algorithm on the Encore Multimax. It is concluded that the formulation of numerical algorithms in terms of the constructs of multilinear algebra, especially the tensor product, together with the coding methods presented, simplifies the writing of the programs for implementing these algorithms. By making the implementation process simpler and more mechanical, one can more easily experiment with and monitor the coding of these algorithms and thereby find better implementations.>