Mal-Netminer: Malware Classification Approach based on Social Network Analysis of System Call Graph

As the security landscape evolves over time, where thousands of species of malicious codes are seen every day, antivirus vendors strive to detect and classify malware families for efficient and effective responses against malware campaigns. To enrich this effort, and by capitalizing on ideas from the social network analysis domain, we build a tool that can help classify malware families using features driven from the graph structure of their system calls. To achieve that, we first construct a system call graph that consists of system calls found in the execution of the individual malware families. To explore distinguishing features of various malware species, we study social network properties as applied to the call graph, including the degree distribution, degree centrality, average distance, clustering coefficient, network density, and component ratio. We utilize features driven from those properties to build a classifier for malware families. Our experimental results show that influence-based graph metrics such as the degree centrality are effective for classifying malware, whereas the general structural metrics of malware are less effective for classifying malware. Our experiments demonstrate that the proposed system performs well in detecting and classifying malware families within each malware class with accuracy greater than 96%.Comment: Mathematical Problems in Engineering, Vol 201

Spacelab system analysis: A study of communications systems for advanced launch systems

An analysis of the required performance of internal avionics data bases for future launch vehicles is presented. Suitable local area networks that can service these requirements are determined

SNA – a toolbox for the stoichiometric analysis of metabolic networks

BACKGROUND: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. RESULTS: SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: . CONCLUSION: Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results

Duration and cost variability of construction activities: an empirical study

The unique nature of construction projects can mean that construction activities often suffer from duration and cost variability. Because this variability is unplanned, it can present a problem when attempting to complete a project on time and on budget. Various factors causing this variability have been identified in the literature, but they predominantly refer to the nature and/or context of the whole project rather than specific activities. In this paper, the order of magnitude of and correlation between activity duration and cost variability is analyzed in 101 construction projects with over 5,000 activities. To do this, the first four moments (mean, standard deviation, skewness, and kurtosis) of actual versus planned duration and cost (log) ratios are analyzed by project, phase of execution, and activity type. Results suggest that, contrary to common wisdom, construction activities do not end late on average. Instead, the large variability in the activity duration is the major factor causing significant project delays and cost overruns. The values of average activity duration and cost variability gathered in this study will also serve as a reference for construction managers to improve future construction planning and project simulation studies with more realistic data

Computational sensor networks

technical reportWe propose Computational Sensor Networks as a methodology to exploit models of physical phenomena in order to better understand the structure of the sensor network. To do so, it is necessary to relate changes in the sensed variables (e.g., temperature) to the aspect of interest in the sensor network (e.g., sensor node position, sensor bias, etc.), and to develop a computational method for its solution. As examples, we describe the use of the heat equation to solve (1) the sensor localization problem, and (2) the sensor bias problem. Simulation and physical experiments are described

Spacelab system analysis: A study of the Marshall Avionics System Testbed (MAST)

An analysis of the Marshall Avionics Systems Testbed (MAST) communications requirements is presented. The average offered load for typical nodes is estimated. Suitable local area networks are determined

Don\u27t Confuse Metatags with Initial Interest Confusion

This Comment focuses on whether the legal doctrine of initial interest confusion should be applied in metatag related trademark infringement cases. The Comment agues that because initial interest confusion does not improve or clarify the existing process of legal inquiry in a trademark infringement litigation, the doctrine is a superfluous legal tool and may even be harmful from a public policy perspective

Public Pensions in the National Accounts and Public Finance Targets

Preparations are underway to revise national accounting to implement actuarial recording of pension liabilities for corporations and government as an employer. This paper extends this to unfunded public pensions with the help of ‘implicit tax’ in pension contributions. The clearest advantages of the revision appear in situations where pension liabilities are shifted from the corporate sector to government, and where part of the public pension system is privatised. The proposed revision raises public debt and deficit to new orders of magnitude. The paper provides a framework for setting the debt and deficit targets under both current and proposed definitions.pensions, public debt and deficit, implicit debt, national accounts