Granular Deleting in Multi Level Security Models – An Electronic Engineering Approach

Thorleuchter, Dirk; Weck, Gerhard; Poel, Dirk Van den

doi:10.1007/978-3-642-31516-9_98

Cited by 10 publications

(8 citation statements)

References 22 publications

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“…We use a methodology that consists of five steps. The first step is to identify scenarios by use of scenario technique [8][9][10][11]. A specific scenario is selected considering the occurrence of terrorism attacks and natural disasters in Germany that represents the environment of a logistic system.…”

Section: Methodsmentioning

confidence: 99%

Improved Emergency Management by a Loosely Coupled Logistic System

Thorleuchter

Schulze

Poel

2012

Communications in Computer and Information Science

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We investigate a robust and intelligent logistic system for emergency management where existing commercial logistic systems are loosely coupled with logistic systems of emergency management organizations and armed forces. This system is used to supply the population in case of a disaster where a high impact of environmental conditions on logistics can be seen. Very important are robustness as the ability of a logistic system to remain effective under these conditions and intelligent behavior for automated ad-hoc decisions facing unforeseen events. Scenario technique, roadmapping, as well as surveys are used as qualitative methodologies to identify current weaknesses in emergency management logistics and to forecast future development of loosely coupled logistic systems. Text mining and web mining analysis as quantitative methodologies are used to improve forecasting. As a result, options are proposed for governmental organizations and companies to enable such a loosely coupled logistic system within the next 20 years.

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Section: Methodsmentioning

confidence: 99%

Improved Emergency Management by a Loosely Coupled Logistic System

Thorleuchter

Schulze

Poel

2012

Communications in Computer and Information Science

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“…We apply a parameter-selection procedure [14] by constructing several rank-k models [15]. A fivefold crossvalidation [16] is used to measure the approximation to A for each rank-k model and the lowest k is selected where the approximation to A is acceptable as defined by a specific threshold [17]. The k column vectors of U represent the latent semantic textual information in form of a parts-based representation.…”

Section: Methodsmentioning

confidence: 99%

Using NMF for Analyzing War Logs

Thorleuchter

Poel

2012

Communications in Computer and Information Science

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Abstract. We investigate a semi-automated identification of technical problems occurred by armed forces weapon systems during mission of war. The proposed methodology is based on a semantic analysis of textual information in reports from soldiers (war logs). Latent semantic indexing (LSI) with non-negative matrix factorization (NMF) as technique from multivariate analysis and linear algebra is used to extract hidden semantic textual patterns from the reports. NMF factorizes the term-by-war log matrix -that consists of weighted term frequencies -into two non-negative matrices. This enables natural parts-based representation of the report information and it leads to an easy evaluation by human experts because human brain also uses parts-based representation. For an improved research and technology planning, the identified technical problems are a valuable source of information. A case study extracts technical problems from military logs of the Afghanistan war. Results are compared to a manual analysis written by journalists of 'Der Spiegel'. Keywords. Non-negative matrix factorization, NMF, Text Mining IntroductionWar logs written by soldiers during mission of war are a valuable source of information. They indicate e.g. technical problems occurred by armed forces weapon systems in use. Considering some of these problems in current research and technology (R&T) projects may be necessary for an increase reliability of future weapon systems. Thus, extracting this feedback from war logs is an important task in R&T planning. We provide a methodology for a semi-automated identification of technical problems in soldiers' war logs. A manual identification of these problems e.g. by human experts is not possible because of the large amount of the logs. Although war logs describe the events of the war, technical problems are just a part of the content e.g. an event is described in detail and besides the malfunction of a weapon system during that event is also mentioned. A frequently occurred malfunction of a specific system in different events can be discovered by identifying the underlying (hidden) semantic textual patterns from the collection of war logs because different soldiers formulize malfunctions by using different words. This excludes the use of text classification

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“…Research projects in this area investigate technologies to apply them in a specific security and defence application field (Thorleuchter, Van den Poel, & Prinzie, 2010b). Thus, some of them may be a profitable target for espionage and they have to be protected from information leakage hazard (Thorleuchter & Van den Poel, 2011c;Thorleuchter, Weck, & Van den Poel, 2012a;Thorleuchter, Weck, & Van den Poel, 2012b).…”

Section: Espionage In Applied Science Randtmentioning

confidence: 99%