Adaptation of the JDL Model for Multi-Sensor National Cyber Security Data Fusion

2016 ◽  
Vol 6 (3) ◽  
pp. 17-30 ◽  
Author(s):  
Ignatius Swart ◽  
Barry Irwin ◽  
Marthie M. Grobler
Keyword(s):  
Data Fusion ◽  
South African ◽  
Cyber Security ◽  
National Level ◽  
Data Sources ◽  
Sensor Data ◽  
Fusion Model ◽  
System A ◽  
Attack Surface

The potential attack surface of a nation is large and no single source of cyber security data provides all the required information to accurately describe the cyber security readiness of a nation. There are a variety of specialised data sources available to assess the state of a nation in key areas such as botnets, spam servers and incorrectly configured hosts. By applying data fusion principles, the potential exists to provide a representative view of all combined data sources. This research will examine a variety of currently available Internet data sources and apply it to an adapted Joint Directors of Laboratories (JDL) data fusion model in order to illustrate the potential gains and current limitations. The JDL model has been adapted to suit national level cyber sensor data fusion with the aim to formally define and reduce data ambiguity and enhance fusion capability in a real world system. A case study highlights the results of applying available open source security information against the model to relate to the current South African cyber landscape.

Adaptation of the JDL Model for Multi-Sensor National Cyber Security Data Fusion

2019 ◽  
pp. 92-107
Author(s):  
Ignatius Swart ◽  
Barry V. W. Irwin ◽  
Marthie M. Grobler
Keyword(s):  
Data Fusion ◽  
South African ◽  
Cyber Security ◽  
National Level ◽  
Data Sources ◽  
Sensor Data ◽  
Fusion Model ◽  
System A ◽  
Attack Surface

The potential attack surface of a nation is large and no single source of cyber security data provides all the required information to accurately describe the cyber security readiness of a nation. There are a variety of specialised data sources available to assess the state of a nation in key areas such as botnets, spam servers and incorrectly configured hosts. By applying data fusion principles, the potential exists to provide a representative view of all combined data sources. This research will examine a variety of currently available Internet data sources and apply it to an adapted Joint Directors of Laboratories (JDL) data fusion model in order to illustrate the potential gains and current limitations. The JDL model has been adapted to suit national level cyber sensor data fusion with the aim to formally define and reduce data ambiguity and enhance fusion capability in a real world system. A case study highlights the results of applying available open source security information against the model to relate to the current South African cyber landscape.

Adaptation of the JDL Model for Multi-Sensor National Cyber Security Data Fusion

2019 ◽  
pp. 311-326
Author(s):  
Ignatius Swart ◽  
Barry V. W. Irwin ◽  
Marthie M. Grobler
Keyword(s):  
Data Fusion ◽  
South African ◽  
Cyber Security ◽  
National Level ◽  
Data Sources ◽  
Sensor Data ◽  
Fusion Model ◽  
System A ◽  
Attack Surface

The potential attack surface of a nation is large and no single source of cyber security data provides all the required information to accurately describe the cyber security readiness of a nation. There are a variety of specialised data sources available to assess the state of a nation in key areas such as botnets, spam servers and incorrectly configured hosts. By applying data fusion principles, the potential exists to provide a representative view of all combined data sources. This research will examine a variety of currently available Internet data sources and apply it to an adapted Joint Directors of Laboratories (JDL) data fusion model in order to illustrate the potential gains and current limitations. The JDL model has been adapted to suit national level cyber sensor data fusion with the aim to formally define and reduce data ambiguity and enhance fusion capability in a real world system. A case study highlights the results of applying available open source security information against the model to relate to the current South African cyber landscape.

scholarly journals Cross-national comparisons of health indicators require standardized definitions and common data sources

2021 ◽  
Vol 79 (1) ◽  
Author(s):  
Hanna Tolonen ◽  
Jaakko Reinikainen ◽  
Päivikki Koponen ◽  
Hanna Elonheimo ◽  
Luigi Palmieri ◽  
...  
Keyword(s):  
Health Care ◽  
National Level ◽  
International Health ◽  
Health Indicators ◽  
Data Sources ◽  
Similar Data ◽  
Prevention And Health Promotion ◽  
Using Data ◽  
Obesity Hypertension

Abstract Background Health indicators are used to monitor the health status and determinants of health of the population and population sub-groups, identify existing or emerging health problems which would require prevention and health promotion activities, help to target health care resources in the most adequate way as well as for evaluation of the success of public health actions both at the national and international level. The quality and validity of the health indicator depends both on available data and used indicator definition. In this study we will evaluate existing knowledge about comparability of different data sources for definition of health indicators, compare how selected health indicators presented in different international databases possibly differ, and finally, present the results from a case study from Finland on comparability of health indicators derived from different data sources at national level. Methods For comparisons, four health indicators were selected that were commonly available in international databases and available for the Finnish case study. These were prevalence of obesity, hypertension, diabetes, and asthma in the adult populations. Our evaluation has three parts: 1) a scoping review of the latest literature, 2) comparison of the prevalences presented in different international databases, and 3) a case study using data from Finland. Results Literature shows that comparability of estimated outcomes for health indicators using different data sources such as self-reported questionnaire data from surveys, measured data from surveys or data from administrative health registers, varies between indicators. Also, the case study from Finland showed that diseases which require regular health care visits such as diabetes, comparability is high while for health outcomes which can remain asymptomatic for a long time such as hypertension, comparability is lower. In different international health related databases, country specific results differ due to variations in the used data sources but also due to differences in indicator definitions. Conclusions Reliable comparison of the health indicators over time and between regions within a country or across the countries requires common indicator definitions, similar data sources and standardized data collection methods.

scholarly journals Hybrid Particle Swarm Optimization for Multi-Sensor Data Fusion

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2792 ◽  
Author(s):  
Hyunseok Kim ◽  
Dongjun Suh
Keyword(s):  
Particle Swarm Optimization ◽  
Data Fusion ◽  
Large Scale ◽  
Synergistic Effects ◽  
Particle Swarm ◽  
Sensor Data ◽  
Fusion Model ◽  
Swarm Optimization ◽  
Hybrid Particle ◽  
Hybrid Particle Swarm Optimization

A hybrid particle swarm optimization (PSO), able to overcome the large-scale nonlinearity or heavily correlation in the data fusion model of multiple sensing information, is proposed in this paper. In recent smart convergence technology, multiple similar and/or dissimilar sensors are widely used to support precisely sensing information from different perspectives, and these are integrated with data fusion algorithms to get synergistic effects. However, the construction of the data fusion model is not trivial because of difficulties to meet under the restricted conditions of a multi-sensor system such as its limited options for deploying sensors and nonlinear characteristics, or correlation errors of multiple sensors. This paper presents a hybrid PSO to facilitate the construction of robust data fusion model based on neural network while ensuring the balance between exploration and exploitation. The performance of the proposed model was evaluated by benchmarks composed of representative datasets. The well-optimized data fusion model is expected to provide an enhancement in the synergistic accuracy.

Remaining useful life prediction based on a multi-sensor data fusion model

2021 ◽  
Vol 208 ◽  
pp. 107249
Author(s):  
Naipeng Li ◽  
Nagi Gebraeel ◽  
Yaguo Lei ◽  
Xiaolei Fang ◽  
Xiao Cai ◽  
...  
Keyword(s):  
Data Fusion ◽  
Life Prediction ◽  
Remaining Useful Life ◽  
Sensor Data ◽  
Fusion Model ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion ◽  
Useful Life

scholarly journals Multi-sensor Data Fusion for Cyber Security Situation Awareness

2011 ◽  
Vol 10 ◽  
pp. 1029-1034 ◽  
Author(s):  
Yan Zhang ◽  
Shuguang Huang ◽  
Shize Guo ◽  
Junmao Zhu
Keyword(s):  
Data Fusion ◽  
Situation Awareness ◽  
Cyber Security ◽  
Sensor Data ◽  
Sensor Data Fusion ◽  
Multi Sensor Data Fusion

Competitive productivity in South African public–private partnerships

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Daniella Fjellstrom ◽  
Paul Frick
Keyword(s):  
South African ◽  
Government Policy ◽  
Research Question ◽  
Qualitative Interviews ◽  
National Level ◽  
Secondary Data ◽  
Content Type ◽  
Moderating Factors ◽  
And Performance

PurposeThis study aims to develop the concept of competitive productivity focussing on the interplay between national competitive productivity (NCP) and firm competitive productivity (FCP) based on the following research question: how does the competitive productivity framework explain the influence that government has on public–private procurement programmes?Design/methodology/approachA case study is conducted on the South African Renewable Energy Independent Power Producer Procurement Programme. Data were collected using an exploratory, mixed methods design, starting with national level secondary data on five bid windows between 2011 and 2014, followed by eight in-depth qualitative interviews with industry experts.FindingsThe findings indicate that non-financial factors, such as trust (through consistent and transparent government policy) as well as a pragmatic attitude on the part of government, increased competition and ultimately resulted in a productive procurement process.Social implicationsBy understanding what moderating factors influence competitiveness in African procurement programmes, using competitive productivity (CP) as a framework, the research contributes to development of government policy and procurement programmes. Incidentally, there is little doubt that improving infrastructure and in turn a greater percentage of access to electricity leads to increased competitiveness of the nation, firms and individuals, thus enabling companies to grow and operate with more stability.Originality/valueOriginality is demonstrated through the interplay of NCP and FCP, where the constructs of culture, benchmarking and performance were found to have the strongest influence of the six constructs of the CP model.

City Data Fusion

2017 ◽  
pp. 398-422 ◽  
Author(s):  
Meisong Wang ◽  
Charith Perera ◽  
Prem Prakash Jayaraman ◽  
Miranda Zhang ◽  
Peter Strazdins ◽  
...  
Keyword(s):  
Data Fusion ◽  
Smart City ◽  
Evaluation Framework ◽  
Data Sources ◽  
Sensor Data ◽  
Research Issues ◽  
Sensor Data Fusion ◽  
Current State ◽  
Diverse Data ◽  
Fusion Framework

Internet of Things (IoT) has gained substantial attention recently and play a significant role in smart city application deployments. A number of such smart city applications depend on sensor fusion capabilities in the cloud from diverse data sources. The authors introduce the concept of IoT and present in detail ten different parameters that govern our sensor data fusion evaluation framework. They then evaluate the current state-of-the art in sensor data fusion against our sensor data fusion framework. The authors' main goal is to examine and survey different sensor data fusion research efforts based on our evaluation framework. The major open research issues related to sensor data fusion are also presented.

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