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Research Interests: Prediction, Flow, Ground Water, Data Bases, Hydrodynamics, and 3 moreAquifers, Accuracy, and Precision
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ABSTRACT [Spanish abstract] Situación actual de los archivos abiertos en el ámbito de las universidades españolas: desarrollo de nuevos proyectos y futuro de los open archives en España. [English abstract] In which situation are the open... more
ABSTRACT [Spanish abstract] Situación actual de los archivos abiertos en el ámbito de las universidades españolas: desarrollo de nuevos proyectos y futuro de los open archives en España. [English abstract] In which situation are the open archives in Spain concretly in the spanish universities, their development and future
Research Interests: Genetic Algorithms, Pattern Recognition, Neural Networks, Neural Network, Multidisciplinary, and 13 moreGenetic Algorithm, Coding, Fault Tolerance, Electricity, Memory, Noise, Error Correction, Encoding, Associative Memory, Fault Tolerant, Hamming Distance, Objective function, and Correlation Matrix
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This paper proposes an innovative data-fusion/ data-mining game theoretic situation awareness and impact assessment approach for cyber network defense. Alerts generated by Intrusion Detection Sensors (IDSs) or Intrusion Prevention Sensors... more
This paper proposes an innovative data-fusion/ data-mining game theoretic situation awareness and impact assessment approach for cyber network defense. Alerts generated by Intrusion Detection Sensors (IDSs) or Intrusion Prevention Sensors (IPSs) are fed into the data refinement (Level 0) and object assessment (L1) data fusion components. High-level situation/threat assessment (L2/L3) data fusion based on Markov game model and Hierarchical Entity Aggregation (HEA) are proposed to refine the primitive prediction generated by adaptive feature/pattern recognition and capture new unknown features. A Markov (Stochastic) game method is used to estimate the belief of each possible cyber attack pattern. Game theory captures the nature of cyber conflicts: determination of the attacking-force strategies is tightly coupled to determination of the defense-force strategies and vice versa. Also, Markov game theory deals with uncertainty and incompleteness of available information. A software tool is developed to demonstrate the performance of the high level information fusion for cyber network defense situation and a simulation example shows the enhanced understating of cyber-network defense.
Research Interests: Game Theory, Data Mining, Situation awareness, Network Security, Data Analysis, and 12 morePattern Recognition, Information Extraction, Stochastic Games, Intrusion Detection, Impact Assessment, Information Fusion, Data Fusion, Intrusion Prevention, Data Processing, Markov Process, Software Tool, and Threat Assessment
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When designing incentive manifolds for use in leader-follower strategies it was previously necessary to use functional analysis approaches or ad hoc methods. This work outlines a new approach which avoids functional analysis in favour of... more
When designing incentive manifolds for use in leader-follower strategies it was previously necessary to use functional analysis approaches or ad hoc methods. This work outlines a new approach which avoids functional analysis in favour of algebraic methods. An incentive affine in both state x and control u is generated; by choosing a free parameter properly the manifold reduces to many
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... Accession Number : ADA124735. Title : Self-Tuning Methods for Multiple-Controller Systems. Descriptive Note : Doctoral thesis,. Corporate ...
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The strategy of data fusion has been applied in threat prediction and situation awareness and the terminology has been standardized by the Joint Directors of Laboratories (JDL) in the form of a so-called JDL Data Fusion Model, which... more
The strategy of data fusion has been applied in threat prediction and situation awareness and the terminology has been standardized by the Joint Directors of Laboratories (JDL) in the form of a so-called JDL Data Fusion Model, which currently called DFIG model. Higher levels of the DFIG model callfor prediction offuture development and awareness of the development of a situation. It is known that Bayesian Network is an insightful approach to determine optimal strategies against asymmetric adversarial opponent. However, it lacks the essential adversarial decision processes perspective. In this paper, a highly innovative data-fusion framework for asymmetric-threat detection and prediction based on advanced knowledge infrastructure and stochastic (Markov) game theory is proposed. In particular, asymmetric and adaptive threats are detected and grouped by intelligent agent and Hierarchical Entity Aggregation in Level 2 and their intents are predicted by a decentralized Markov (stochastic) game model with deception in Level 3. We have verified that our proposed algorithms are scalable, stable, and perform satisfactorily according to the situation awareness performance metric.