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67
Control Flow Obfuscation using Neural Network to Fight Concolic Testing?
"... Abstract. Concolic testing is widely regarded as the state-of-the-art technique in dynamic discovering and analyzing trigger-based behavior in software programs. It uses symbolic execution and an automatic the-orem prover to generate new concrete test cases to maximize code cover-age for scenarios l ..."
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Abstract. Concolic testing is widely regarded as the state-of-the-art technique in dynamic discovering and analyzing trigger-based behavior in software programs. It uses symbolic execution and an automatic the-orem prover to generate new concrete test cases to maximize code cover-age for scenarios
systems using neural networks
, 2004
"... This paper presents a development and implementation of a PC-based maximum power point tracker (MPPT) for PV system using neural networks (NN). The system consists of a PV module via a MPPT supplying a dc motor that drives an air fan. The control algorithm is developed to use the artificial NN for d ..."
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This paper presents a development and implementation of a PC-based maximum power point tracker (MPPT) for PV system using neural networks (NN). The system consists of a PV module via a MPPT supplying a dc motor that drives an air fan. The control algorithm is developed to use the artificial NN
A Fast Static Analysis Approach to Detect Exploit Code Inside Network Flows
- In RAID
, 2005
"... Abstract. A common way by which attackers gain control of hosts is through remote exploits. A new dimension to the problem is added by worms which use exploit code to self-propagate, and are becoming a commonplace occurrence. Defense mechanisms exist but popular ones are signature-based techniques w ..."
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Cited by 55 (0 self)
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which use known byte patterns, and they can be thwarted using polymorphism, metamorphism and other obfuscations. In this paper, we argue that exploit code is characterized by more than just a byte pattern because, in addition, there is a definite control and data flow. We propose a fast static analysis
Control of Subsonic Cavity Flows by Neural Networks – Analytical Models and Experimental Validation
"... Flow control is attracting an increasing attention of researchers from a wide spectrum of specialties because of its interdisciplinary nature and the associated challenges. One of the main goals of The Collaborative Center of Control Science at The Ohio State University is to bring together research ..."
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Cited by 3 (1 self)
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researchers from different disciplines to advance the science and technology of flow control. This paper approaches the control of subsonic cavity flow, a study case we have selected, from a computational intelligence point of view, and offers a solution that displays an interconnected neural architecture
An Open Flow Controller Based on the Intercerebral Neural Network for Media Independent Handover
"... Copyright: © 2014 Wu Q, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. This paper presents a novel open ..."
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controller equation for the media independent handover that are mixed with the radial and sigmoid activation functions of the intercerebral neural network. Simulations based on the field experiment test data show that the system using the swarm intelligence algorithm is practical for the improvement
Exploring and Evolving Process-oriented Control for Real and Virtual Fire Fighting Robots
"... Current research in evolutionary robotics is largely focused on creating controllers by either evolving neural networks or refining genetic programs based on grammar trees. We propose the use of the dataflow languages for the construction of effective robotic controllers and the evolution of new con ..."
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Current research in evolutionary robotics is largely focused on creating controllers by either evolving neural networks or refining genetic programs based on grammar trees. We propose the use of the dataflow languages for the construction of effective robotic controllers and the evolution of new
Mastitis detection in dairy cows using Neural Networks
"... Abstract: The aim of the present research was to investigate the usefulness of neural networks (NN) in the early detection and control of mastitis in cows milked in an automatic milking system. A data set of 403,537 milkings involving 478 cows was used. Mastitis was determined according to udder tre ..."
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Abstract: The aim of the present research was to investigate the usefulness of neural networks (NN) in the early detection and control of mastitis in cows milked in an automatic milking system. A data set of 403,537 milkings involving 478 cows was used. Mastitis was determined according to udder
Numerical Simulation of Neural Network-Controlled Unmanned Undersea Vehicle
- WSEAS Transactions on Circuits and Systems
, 2003
"... Abstract:- In this paper, the locomotion of an autonomously navigated undersea vehicle that uses vorticity control propulsion is computationally simulated. The navigation procedure employs a set of vehicle geometric and state variables to predict the needed vehicle body deformations in order to pass ..."
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Cited by 2 (0 self)
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of unsteady flow standard test cases. Then, another set of properly planned test cases to cover the range of possible conditions were processed with the simulation and the output data was subsequently used to train a Multi-Layer Perceptron (MLP) neural network. The trained network can predict what body
An Emergency Department Simulation and a Neural Network Metamodel
"... This paper describes a discrete event stochastic simulation of a hospital emergency department, and the development of a metamodel of that simulation. The metamodeling technique used is artificial neural networks, which are trained using the output of the simulation. The performance of the neural ..."
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This paper describes a discrete event stochastic simulation of a hospital emergency department, and the development of a metamodel of that simulation. The metamodeling technique used is artificial neural networks, which are trained using the output of the simulation. The performance
Neural Control of Helicopter Blade-Vortex Interaction Noise
"... Significant reduction of helicopter blade-vortex interaction (BVI) noise is currently one of the most advanced research topics in the helicopter industry. This is due to the complex flow, the close aerodynamic and structural coupling, and the interaction of the blades with the trailing edge vortices ..."
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vortices. Analytical and numerical modelling techniques are therefore currently still far from a sufficient degree of accuracy to obtain satisfactory results using classical model based control concepts. Neural networks with a proven potential to learn nonlinear relationships implicitly encoded in a
Results 1 - 10
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