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Creating a cyber moving target for critical infrastructure applications using platform diversity

January 28, 2012
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Journal Article
Author:
Hamed Okhravi
…
Published in:
Int. J. of Critical Infrastructure Protection, Vol. 5, No. 1, March 2012, pp. 30-39.
Topic:
systems architecture
R&D area:
R&D group:

Summary

Despite the significant effort that often goes into securing critical infrastructure assets, many systems remain vulnerable to advanced, targeted cyber attacks. This paper describes the design and implementation of the Trusted Dynamic Logical Heterogeneity System (TALENT), a framework for live-migrating critical infrastructure applications across heterogeneous platforms. TALENT permits a running critical application to change its hardware platform and operating system, thus providing cyber survivability through platform diversity. TALENT uses containers (operating-system-level virtualization) and a portable checkpoint compiler to create a virtual execution environment and to migrate a running application across different platforms while preserving the state of the application (execution state, open files and network connections). TALENT is designed to support general applications written in the C programming language. By changing the platform on-the-fly, TALENT creates a cyber moving target and significantly raises the bar for a successful attack against a critical application. Experiments demonstrate that a complete migration can be completed within about one second.
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Summary

Despite the significant effort that often goes into securing critical infrastructure assets, many systems remain vulnerable to advanced, targeted cyber attacks. This paper describes the design and implementation of the Trusted Dynamic Logical Heterogeneity System (TALENT), a framework for live-migrating critical infrastructure applications across heterogeneous platforms. TALENT permits a running...

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Creating a cyber moving target for critical infrastructure applications using platform diversity

Estimation of New York departure fix capacities in fair and convective weather

January 23, 2012
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Conference Paper
Author:
Ngaire K. Underhill
Published in:
3rd Aviation, Range, and Aerospace Meteorology, 23 January 2012.
Topic:
air traffic management
R&D area:
R&D group:

Summary

When convective weather impacts the New York Metro airspace, traffic managers may employ several tactics to mitigate weather impacts and maintain manageable and efficient flow of traffic to and from the airports. These tactics, which include maneuvering individual flights through weather, merging and redirecting traffic flows to avoid storms, and rerouting traffic from blocked routes onto unimpacted or less-impacted routes, all affect the capacity of the affected airspace resources (departure fixes, routes, or gates). Furthermore, the location of the weather impacts can have a great influence on the amount of leeway that traffic managers have in applying these tactics. In New York, departure fixes, the gateways to en route airspace where departure traffic from several metroplex airports are merged onto en route airways, are particularly critical. When congestion (volume of traffic in excess of capacity) occurs near departure fixes as a result of weather impacts, traffic managers must resort to airborne holding or unplanned departure stops to quickly reduce traffic over the fix to manageable levels. Nonetheless, when convective weather impacts densely packed and busy metroplex airspaces, it is inevitable that traffic will need to use impacted departure fixes and routes to keep delays in check. For this reason, predictions of the weather-impacted capacity of critical airspace resources like departure fixes that are based in the reality of commonly used impact mitigation tactics, are needed to help traffic managers anticipate and avoid disruptive congestion at weather-impacted departure fixes. The Route Availability Planning Tool (RAPT) is a departure management decision support tool that has been used in the New York operations since 2003. It predicts the weather impact on departure fixes and routes based on departure times. RAPT assigns a departure status (RED, YELLOW, or GREEN) to individual departure routes based on the departure time, the predicted severity of the convective weather that will impact the route, the likelihood that a pilot will deviate to avoid the weather along the route, and the operational sensitivity to deviations in the departure airspace that the route traverses. These blockages assist traffic managers in prompt route reopening of routes closed by convective weather impacts, as well as providing situational awareness for impeding impacts on routes. RAPT also identifies the location of weather impacts along the departure route. This paper presents an analysis of observed fair weather and convective weather impacted throughput on New York departure fixes. RAPT departure status and impact location are used to characterize the severity of departure fix weather impacts, and weather-impacted fix capacity ranges are estimated as a function of RAPT impacts. The use of traffic flow merging is identified, and weather impacted capacity ranges for commonly used merged flows are also estimated.
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Summary

When convective weather impacts the New York Metro airspace, traffic managers may employ several tactics to mitigate weather impacts and maintain manageable and efficient flow of traffic to and from the airports. These tactics, which include maneuvering individual flights through weather, merging and redirecting traffic flows to avoid storms, and...

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Estimation of New York departure fix capacities in fair and convective weather

A tree-based ensemble method of the prediction and uncertainty quantification of aircraft landing times

January 22, 2012
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Conference Paper
Author:
Yan Glina
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Published in:
10th Conf. on Artificial and Computational Intelligence, 22 January 2012.
Topic:
air traffic control
R&D area:
R&D group:

Summary

Accurate aircraft landing time predictions provide situational awareness for air traffic controllers, enable decision support algorithms and gate management planning. This paper presents a new approach for estimation of landing times using a tree-based ensemble method, namely Quantile Regression Forests. This method is suitable for real-time applications, provides robust and accurate predictions of landing times, and yields prediction intervals for individual flights, which provide a natural way of quantifying uncertainty. The approach was tested for arrivals at Dallas/Fort Worth International Airport over a range of days with a variety of operational conditions.
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Summary

Accurate aircraft landing time predictions provide situational awareness for air traffic controllers, enable decision support algorithms and gate management planning. This paper presents a new approach for estimation of landing times using a tree-based ensemble method, namely Quantile Regression Forests. This method is suitable for real-time applications, provides robust and...

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A tree-based ensemble method of the prediction and uncertainty quantification of aircraft landing times

A new approach for designing safer collision avoidance systems

January 1, 2012
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Journal Article
Author:
Mykel J. Kochenderfer
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Published in:
Air Traffic Control Q., Vol. 20, No. 1, January 2012, pp. 27-45.
Topic:
collision avoidance
R&D area:
R&D group:

Summary

The Traffic Alert and Collision Avoidance System significantly reduces the risk of mid-air collision and is mandated worldwide on transport aircraft. Engineering the avoidance logic was costly and spanned decades. The development followed an iterative process where the logic was specified using pseudocode, evaluated in simulation, and revised based on performance against a set of metrics. Modifying the logic is difficult because the pseudocode contains many heuristic rules that interact in complex ways. With the introduction of next-generation air traffic control procedures and surveillance systems, the logic will require significant revision to prevent unnecessary alerts. Recent work has explored an approach for designing collision avoidance systems that will shorten the development cycle, improve maintainability, and enhance safety with fewer false alerts. The approach involves computationally deriving optimized logic from encounter models and performance metrics. This paper outlines the approach and discusses the anticipated impact on development, safety, and operation.
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Summary

The Traffic Alert and Collision Avoidance System significantly reduces the risk of mid-air collision and is mandated worldwide on transport aircraft. Engineering the avoidance logic was costly and spanned decades. The development followed an iterative process where the logic was specified using pseudocode, evaluated in simulation, and revised based on...

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A new approach for designing safer collision avoidance systems

Fundamental Questions in the Analysis of Large Graphs

January 1, 2012
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Book Chapter
Author:
Jeremy Kepner
…
Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 353-357.
Topic:
graph processing
R&D area:
R&D group:

Summary

Graphs are a general approach for representing information that spans the widest possible range of computing applications. They are particularly important to computational biology, web search, and knowledge discovery. As the sizes of graphs increase, the need to apply advanced mathematical and computational techniques to solve these problems is growing dramatically. Examining the mathematical and computational foundations of the analysis of large graphs generally leads to more questions than answers. This book concludes with a discussion of some of these questions.
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Summary

Graphs are a general approach for representing information that spans the widest possible range of computing applications. They are particularly important to computational biology, web search, and knowledge discovery. As the sizes of graphs increase, the need to apply advanced mathematical and computational techniques to solve these problems is growing...

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Fundamental Questions in the Analysis of Large Graphs

Subgraph Detection

January 1, 2012
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Book Chapter
Author:
Jeremy Kepner
Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 115-133.
Topic:
graph processing
R&D area:
R&D group:

Summary

Detecting subgraphs of interest in larger graphs is the goal of many graph analysis techniques. The basis of detection theory is computing the probability of a “foreground” with respect to a model of the “background” data. Hidden Markov Models represent one possible foreground model for patterns of interaction in a graph. Likewise, Kronecker graphs are one possible model for power law background graphs. Combining these models allows estimates of the signal to noise ratio, probability of detection, and probability of false alarm for different classes of vertices in the foreground. These estimates can then be used to construct filters for computing the probability that a background graph contains a particular foreground graph. This approach is applied to the problem of detecting a partially labeled tree graph in a power law background graph. One feature of this method is the ability to a priori estimate the number of vertices that will be detected via the filter.
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Summary

Detecting subgraphs of interest in larger graphs is the goal of many graph analysis techniques. The basis of detection theory is computing the probability of a “foreground” with respect to a model of the “background” data. Hidden Markov Models represent one possible foreground model for patterns of interaction in a...

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Subgraph Detection

Linear algebraic notation and definitions

January 1, 2012
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Book Chapter
Author:
Eric I. Robinson
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Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 13-18.
Topic:
algorithms
R&D area:
R&D group:

Summary

This chapter presents notation, definitions, and conventions for graphs, matrices, arrays, and operations upon them.
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Summary

This chapter presents notation, definitions, and conventions for graphs, matrices, arrays, and operations upon them.

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Linear algebraic notation and definitions

A knowledge-based operator for a genetic algorithm which optimizes the distribution of sparse matrix data

January 1, 2012
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Book Chapter
Author:
Una-May O'Reilly
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Published in:
Parallel Architectures and Bioinspired Algorithms
Topic:
algorithms
R&D area:
R&D group:

Summary

We present the Hogs and Slackers genetic algorithm (GA) which addresses the problem of improving the parallelization efficiency of sparse matrix computations by optimally distributing blocks of matrices data. The performance of a distribution is sensitive to the non-zero patterns in the data, the algorithm, and the hardware architecture. In a candidate distributions the Hogs and Slackers GA identifies processors with many operations – hogs, and processors with fewer operations – slackers. Its intelligent operation-balancing mutation operator then swaps data blocks between hogs and slackers to explore a new data distribution.We show that the Hogs and Slackers GA performs better than a baseline GA. We demonstrate Hogs and Slackers GA’s optimization capability with an architecture study of varied network and memory bandwidth and latency.
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Summary

We present the Hogs and Slackers genetic algorithm (GA) which addresses the problem of improving the parallelization efficiency of sparse matrix computations by optimally distributing blocks of matrices data. The performance of a distribution is sensitive to the non-zero patterns in the data, the algorithm, and the hardware architecture. In...

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A knowledge-based operator for a genetic algorithm which optimizes the distribution of sparse matrix data

Visualizing Large Kronecker Graphs

January 1, 2012
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Book Chapter
Author:
Huy T. Nguyen
…
Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 241-250.
Topic:
graph processing
R&D area:
R&D group:

Summary

Kronecker graphs have been shown to be one of the most promising models for real-world networks. Visualization of Kronecker graphs is an important challenge. This chapter describes an interactive framework to assist scientists and engineers in generating, analyzing, and visualizing Kronecker graphs with as little effort as possible.
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Summary

Kronecker graphs have been shown to be one of the most promising models for real-world networks. Visualization of Kronecker graphs is an important challenge. This chapter describes an interactive framework to assist scientists and engineers in generating, analyzing, and visualizing Kronecker graphs with as little effort as possible.

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Visualizing Large Kronecker Graphs

The Kronecker theory of power law graphs

January 1, 2012
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Book Chapter
Author:
Jeremy Kepner
Published in:
Graph Algorithms in the Language of Linear Algebra, pp. 205-220.
Topic:
graph processing
R&D area:
R&D group:

Summary

An analytical theory of power law graphs is presented based on the Kronecker graph generation technique. Explicit, stochastic, and instance Kronecker graphs are used to highlight different properties. The analysis uses Kronecker exponentials of complete bipartite graphs to formulate the substructure of such graphs. The Kronecker theory allows various high-level quantities (e.g., degree distribution, betweenness centrality, diameter, eigenvalues, and iso-parametric ratio) to be computed directly from the model parameters.
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Summary

An analytical theory of power law graphs is presented based on the Kronecker graph generation technique. Explicit, stochastic, and instance Kronecker graphs are used to highlight different properties. The analysis uses Kronecker exponentials of complete bipartite graphs to formulate the substructure of such graphs. The Kronecker theory allows various high-level...

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The Kronecker theory of power law graphs
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