• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.159-167
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• 2023

Objective: • To detect black hole and warm hole attacks in wireless sensor networks. • To give a solution for energy depletion and security breach in wireless sensor networks. • To address the security problem using strategic decision support system. Methods: The proposed stackelberg game is used to make the spirited relations between multi leaders and multi followers. In this game, all cluster heads are acts as leaders, whereas agent nodes are acts as followers. The game is initially modeled as Quadratic Programming and also use backtracking search optimization algorithm for getting threshold value to determine the optimal strategies of both defender and attacker. Findings: To find optimal payoffs of multi leaders and multi followers are based on their utility functions. The attacks are easily detected based on some defined rules and optimum results of the game. Finally, the simulations are executed in matlab and the impacts of detection of black hole and warm hole attacks are also presented in this paper. Novelty: The novelty of this study is to considering the stackelberg game with backtracking search optimization algorithm (BSOA). BSOA is based on iterative process which tries to minimize the objective function. Thus we obtain the better optimization results than the earlier approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.7
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• pp.1721-1736
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• 2013

Black and gray hole attack is one kind of routing disturbing attacks and can bring great damage to the network. As a result, an efficient algorithm to detect black and gray attack is important. This paper demonstrate an adaptive approach to detecting black and gray hole attacks in ad hoc network based on a cross layer design. In network layer, we proposed a path-based method to overhear the next hop's action. This scheme does not send out extra control packets and saves the system resources of the detecting node. In MAC layer, a collision rate reporting system is established to estimate dynamic detecting threshold so as to lower the false positive rate under high network overload. We choose DSR protocol to test our algorithm and ns-2 as our simulation tool. Our experiment result verifies our theory: the average detection rate is above 90% and the false positive rate is below 10%. Moreover, the adaptive threshold strategy contributes to decrease the false positive rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5574-5591
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• 2017

Inspired by the idea of Artificial Immune System, many researches of wireless sensor network (WSN) intrusion detection is based on the artificial intelligent system (AIS). However, a large number of generated detectors, black hole, overlap problem of NSA have impeded further used in WSN. In order to improve the anomaly detection performance for WSN, detector generation mechanism need to be improved. Therefore, in this paper, a Differential Evolution Constraint Multi-objective Optimization Problem based Negative Selection Algorithm (DE-CMOP based NSA) is proposed to optimize the distribution and effectiveness of the detector. By combining the constraint handling and multi-objective optimization technique, the algorithm is able to generate the detector set with maximized coverage of non-self space and minimized overlap among detectors. By employing differential evolution, the algorithm can reduce the black hole effectively. The experiment results show that our proposed scheme provides improved NSA algorithm in-terms, the detectors generated by the DE-CMOP based NSA more uniform with less overlap and minimum black hole, thus effectively improves the intrusion detection performance. At the same time, the new algorithm reduces the number of detectors which reduces the complexity of detection phase. Thus, this makes it suitable for intrusion detection in WSN.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.139-144
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• 2024

VANETs have become one of the most attractive research areas in the world of wireless networks in recent years. Indeed, vehicular networks have become capable of optimizing road traffic, which significantly reduces the number of accidents through notifications exchanged between nearby vehicles. The routing function based on the opportunistic algorithm is a critical part of the vehicle's communication system and will therefore be an ideal target for attacks that could aim to prevent alert messages from reaching their destination, and thus endanger human lives. The black hole attack is a major threat to the security of VANETs. The main idea of this paper focuses on the analysis of this type of attack in VANETs using Discrete-Time Markov Chains (DTMC). and deduce at the end the effect of the number of malicious nodes on the delivery rate in the network.

• Smart Structures and Systems
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• v.29 no.3
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• pp.513-522
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• 2022

Due to the importance of accurate analysis of bearing capacity in civil engineering projects, this paper studies the efficiency of two novel metaheuristic-based models for this objective. To this end, black hole algorithm (BHA) and multi-verse optimizer (MVO) are synthesized with an artificial neural network (ANN) to build the proposed hybrid models. Based on the settlement of a two-layered soil (and a shallow footing) system, the stability values (SV) of 0 and 1 (indicating the stability and failure, respectively) are set as the targets. Each model predicted the SV for 901 stages. The results indicated that the BHA and MVO can increase the accuracy (i.e., the area under the receiving operating characteristic curve) of the ANN from 94.0% to 96.3 and 97.2% in analyzing the SV pattern. Moreover, the prediction accuracy rose from 93.1% to 94.4 and 95.0%. Also, a comparison between the ANN's error decreased by the BHA and MVO (7.92% vs. 18.08% in the training phase and 6.28% vs. 13.62% in the testing phase) showed that the MVO is a more efficient optimizer. Hence, the suggested MVO-ANN can be used as a reliable approach for the practical estimation of bearing capacity.

• Journal of the Korean earth science society
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• v.45 no.4
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• pp.292-303
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• 2024

We study quasi-spherical, supersonic accretion flows around black holes using high-accuracy numerical simulations. We describe a code, the Lagrangian Total Variation Diminishing (TVD), and a remap routine to address a specific issue in the Advection Dominated Accretion Flow (ADAF) that is, appropriately handling the angular momentum even near the inner boundary. The Lagrangian TVD code is based on an explicit finite difference scheme on mass-volume grids to track fluid particles with time. The consequences are remapped on fixed grids using the explicit Eulerian finite-difference algorithm with a third-order accuracy. Test results show that one can successfully handle flows and resolve shocks within two to three computational cells. Especially, the calculation of a hydrodynamical accretion disk without viscosity around a black hole shows that one can conserve nearly 100% of specific a ngular momentum in one-and two-dimensional cylindrical coordinates. Thus, we apply this code to obtain a numerically similar ADAF solution. We perform simulations, including viscosity terms in one-dimensional spherical geometry on the non-uniform grids, to obtain greater quantitative consequences and to save computational time. The error of specific angular momentum in Newtonian potential is less than 1% between r~10r_s and r~10⁴ r_s, where r_s is sink size. As Narayan et al. (1997) suggested, the ADAFs in pseudo-Newtonian potential become supersonic flows near the black hole, and the sonic point is r_sonic~5.3r_g for flow with α =0.3 and γ=1 .5. Such simulations indicate that even the ADAF with γ=5/3 is differentially rotating, as Ogilvie (1999) indicated. Hence, we conclude that the Lagrangian TVD and remap code treat the role of viscosity more precisely than the other scheme, even near the inner boundary in a rotating accretion flow around a nonrotating black hole.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.51.3-52
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• 2020

We present the status of the development of a Markov Chain Monte Carlo (MCMC) parameter estimation (PE) pipeline for compact binary coalescences (CBCs) with the Japanese KAGRA gravitational-wave (GW) detector. The pipeline is included in the KAGRA Algorithm Library (KAGALI). Basic functionalities are benchmarked from the LIGO Algorithm Library (LALSuite) but the KAGRA MCMC PE pipeline will provide a simpler, memory-efficient pipeline to estimate physical parameters from gravitational waves emitted from compact binaries consisting of black holes or neutron stars. Applying inspiral-merge-ringdown and inspiral waveforms, we performed simulations of various black hole binaries, we performed the code sanity check and performance test. In this talk, we present the situation of GW observation with the Covid-19 pandemic. In addition to preliminary PE results with the KAGALI MCMC PE pipeline, we discuss how we can optimize a CBC PE pipeline toward the next observation run.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.61.1-61.1
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• 2016

Black hole (BH) mass is a fundamental quantity to understand BH growth, galaxy evolution, and connection between them. Thus, obtaining accurate and precise BH mass estimates over cosmic time is of paramount importance. The rest-frame UV CIV ${\lambda}1549$ broad emission line is commonly used for BH mass estimates in high-redshift AGNs (i.e., $2{\leq}z{\leq}5$) when single-epoch (SE) optical spectra are available. Achieving correct and accurate calibration for CIV-based SE BH mass estimators against the most reliable reverberation-mapping based BH mass estimates is thus practically important and still useful. By performing multi-component spectral decomposition analysis to obtained high-quality HST UV spectra for the updated sample of local reverberation-mapped AGNs including new HST STIS observations, CIV emission line widths and continuum luminosities are consistently measured. Using a Bayesian hierarchical model with MCMC sampling based on Hamiltonian Monte Carlo algorithm (Stan NUTS), we provide the most consistent and accurate calibration of CIV-based BH mass estimators for the three line width characterizations, i.e., full width at half maximum (FWHM), line dispersion (${\sigma}_{line}$), and mean absolute deviation (MAD), in the extended BH mass dynamic range of log $M_{BH}/M_{\odot}=6.5-9.1$.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.91-97
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• 2000

In this paper, the illuminator is designed to recognize the shape and the existence of holes of radiation fin in the point that the light reflection characteristics are different according to the roughness of the material. The threshold value, the positions of holes and the black pixel nembers in the positon are obtained under the illuminator, in accordance with the reference image, by applying binary conversion and hole segmentation algorithm, as they are suggested in this paper, The existence and shape of hole are recognized by calculating the distance and feature value in the test image, which is obtained from the parameters of reference image. It is programmed to apply to GUI(Graphic User the Interface) in windows. More than 98% of recognition rate is shown, as it is applied to three different sizes of the radiation fin.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.655-662
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• 2016

We investigated on the usefulness of MAR algorithm by making a comparison of the CT value between before and after applying the MAR algorithm in dual energy CT, using the various kinds of medical metals, causing the artifact to lead to the low image quality. As a result, the artifact was reduced in most cases (P<0.05); in particular, the artifact was highly reduced (P<0.05) using high density material, like alloy-stainless (reduced by 78.1%) and platinum, for example GDC coil (reduced by 76.1%). The effect of decreasing the Black hole artifact was outstanding in both the alloy-stainless and alloy-titanium (P<0.05). However, in case of GDC coil-a type platinum, white streak artifact was reduced effectively (P<0.05). Therefore, in case of patients who have medical metals inserted, we think that high-quality image information can be provided by decreasing the artifact caused by high density material through MAR algorithm in dual energy CT.