• Title/Summary/Keyword: Attack Model

Search Result 1,005, Processing Time 0.035 seconds

Enhanced Differential Power Analysis based on the Generalized Signal Companding Methods (일반화된 신호 압신법에 기반한 향상된 차분전력분석 방법)

  • Choi, Ji-Sun;Ryoo, Jeong-Choon;Han, Dong-Guk;Park, Tae-Hoon
    • The KIPS Transactions:PartC
    • /
    • v.18C no.4
    • /
    • pp.213-216
    • /
    • 2011
  • Differential Power Analysis is fully affected by various noises including temporal misalignment. Recently, Ryoo et al have introduced an efficient preprocessor method leading to improvements in DPA by removing the noise signals. This paper experimentally proves that the existing preprocessor method is not applied to all processor. To overcome this defect, we propose a Differential Trace Model(DTM). Also, we theoretically prove and experimentally confirm that the proposed DTM suites DPA.

Modeling and Tracking Simulation of ROV for Bottom Inspection of a Ship using Component Drag Model (요소항력모델을 활용한 선저검사용 ROV 모델링 및 트래킹 시뮬레이션)

  • Jeon, MyungJun;Lee, DongHyun;Yoon, Hyeon Kyu;Koo, Bonguk
    • Journal of Ocean Engineering and Technology
    • /
    • v.30 no.5
    • /
    • pp.374-380
    • /
    • 2016
  • The large drift and angle of attack motion of an ROV (Remotely operated vehicle) cannot be modeled using the typical hydrodynamic coefficients of conventional straight running AUVs and specific slender bodies. In this paper, the ROV hull is divided into several simple-shaped components to model the hydrodynamic force and moment. The hydrodynamic force and moment acting on each component are modeled as the components of added mass force and drag using the known values for simple shapes such as a cylinder and flat plate. Since an ROV is operated under the water, the only environmental force considered is the current effect. The target ROV dealt with in this paper has six thrusters, and it is assumed that its maneuvering motion is determined using a thrust allocation algorithm. Tracking simulations are carried out on the ship’s surface near the stern, bow, and midship sections based on the modeling of the hydrodynamic force and current effect.

Numerical simulation approach for structural capacity of corroded reinforced concrete bridge

  • Zhou, Xuhong;Tu, Xi;Chen, Airong;Wang, Yuqian
    • Advances in concrete construction
    • /
    • v.7 no.1
    • /
    • pp.11-22
    • /
    • 2019
  • A comprehensive assessing approach for durability of reinforced concrete structures dealing with the corrosion process of rebar subjected to the attack of aggressive agent from environment was proposed in this paper. Corrosion of rebar was suggested in the form of combination of global corrosion and pitting. Firstly, for the purposed of considering the influence of rebar's radius, a type of Plane Corrosion Model (PCM) based on uniform corrosion of rebar was introduced. By means of FE simulation approach, global corrosion process of rebar regarding PCM and LCM (Linear Corrosion Model) was regressed and compared according to the data from Laboratoire $Mat{\acute{e}}riaux$ et $Durabilit{\acute{e}}$ des Constructions (LMDC). Secondly, pitting factor model of rebar in general descend law with corrosion degree was introduced in terms of existing experimental data. Finally, with the comprehensive numerical simulation, the durability of an existing arch bridge was studied in depth in deterministic way, including diffusion process and sectional strength of typical cross section of arch, crossbeam and deck slab. Evolution of structural capacity considering life-cycle rehabilitation strategy indicated the degradation law of durability of reinforced arch bridges.

Forecasting Foreign Visitors using SARIMAX Models with the Exogenous Variable of Demand Decrease (수요감소 요인 외생변수를 갖는 SARIMAX 모형을 이용한 관광수요 예측)

  • Lee, Geun-Cheol;Choi, Seong-Hoon
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.43 no.4
    • /
    • pp.59-66
    • /
    • 2020
  • In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).

Shape optimization of corner recessed square tall building employing surrogate modelling

  • Arghyadip Das;Rajdip Paul;Sujit Kumar Dalui
    • Wind and Structures
    • /
    • v.36 no.2
    • /
    • pp.105-120
    • /
    • 2023
  • The present study is performed to find the effect of corner recession on a square plan-shaped tall building. A series of numerical simulations have been carried out to find the two orthogonal wind force coefficients on various model configurations using Computational Fluid Dynamics (CFD). Numerical analyses are performed by using ANSYS-CFX (k-ℇ turbulence model) considering the length scale of 1:300. The study is performed for 0° to 360° wind angle of attack. The CFD data thus generated is utilised to fit parametric equations to predict alongwind and crosswind force coefficients, Cfx and Cfy. The precision of the parametric equations is validated by employing a wind tunnel study for the 40% corner recession model, and an excellent match is observed. Upon satisfactory validation, the parametric equations are further used to carry out multiobjective optimization considering two orthogonal force coefficients. Pareto optimal design results are presented to propose suitable percentages of corner recession for the study building. The optimization is based on reducing the alongwind and crosswind forces simultaneously to enhance the aerodynamic performance of the building.

Analyzing Key Variables in Network Attack Classification on NSL-KDD Dataset using SHAP (SHAP 기반 NSL-KDD 네트워크 공격 분류의 주요 변수 분석)

  • Sang-duk Lee;Dae-gyu Kim;Chang Soo Kim
    • Journal of the Society of Disaster Information
    • /
    • v.19 no.4
    • /
    • pp.924-935
    • /
    • 2023
  • Purpose: The central aim of this study is to leverage machine learning techniques for the classification of Intrusion Detection System (IDS) data, with a specific focus on identifying the variables responsible for enhancing overall performance. Method: First, we classified 'R2L(Remote to Local)' and 'U2R (User to Root)' attacks in the NSL-KDD dataset, which are difficult to detect due to class imbalance, using seven machine learning models, including Logistic Regression (LR) and K-Nearest Neighbor (KNN). Next, we use the SHapley Additive exPlanation (SHAP) for two classification models that showed high performance, Random Forest (RF) and Light Gradient-Boosting Machine (LGBM), to check the importance of variables that affect classification for each model. Result: In the case of RF, the 'service' variable and in the case of LGBM, the 'dst_host_srv_count' variable were confirmed to be the most important variables. These pivotal variables serve as key factors capable of enhancing performance in the context of classification for each respective model. Conclusion: In conclusion, this paper successfully identifies the optimal models, RF and LGBM, for classifying 'R2L' and 'U2R' attacks, while elucidating the crucial variables associated with each selected model.

Research on Cyber Kill Chain Models for Offensive Cyber Operations (공세적 사이버 작전을 위한 사이버 킬체인 모델 연구)

  • Seong Bae Jo;Wan Ju Kim;Jae Sung Lim
    • Convergence Security Journal
    • /
    • v.23 no.4
    • /
    • pp.71-80
    • /
    • 2023
  • Cyberspace has emerged as the fifth domain of warfare, alongside land, sea, air, and space. It has become a crucial focus for offensive and defensive military operations. Governments worldwide have demonstrated their intent to engage in offensive cyber operations within this domain. This paper proposes an innovative offensive cyber kill chain model that integrates the existing defensive strategy, the cyber kill chain model, with the joint air tasking order (ATO) mission execution cycle and joint target processing procedure. By combining physical and cyber operations within a joint framework, this model aims to enhance national cyber operations capabilities at a strategic level. The integration of these elements seeks to address the evolving challenges in cyberspace and contribute to more effective jointness in conducting cyber operations.

Practical applications of computational fluid dynamics to wind design of high-rise buildings

  • Min Kyu Kim;Soonpil Kang;Thomas H.-K. Kang
    • Wind and Structures
    • /
    • v.39 no.4
    • /
    • pp.287-304
    • /
    • 2024
  • An accurate assessment of aerodynamic effects on structures is essential for a reliable wind design for high-rise buildings. Turbulence model is a key ingredient of computational fluid dynamics (CFD) in calculating the wind flow fields. This paper aims to identify the properties of representative RANS and LES models particularly for wind load determination. The models investigated are the realizable k-ε model for RANS and the dynamic Smagorinsky model for LES. In this study, their application aspects are discussed to provide enhanced reproducibility and reliability. The airflow around a building at Reynolds number 76,000 is simulated and the numerical results are also compared with wind tunnel experiment data. The wind design loads, such as story shear forces and overturning or torsional moments, are calculated based on the numerical results. Both RANS and LES models accurately capture surface pressure profiles, while LES results demonstrate proper energy decay in the power spectra. The numerical results highlight the effects of aspect ratio of building and the attack angle on the wind loads. This information would be of great help in designing tall buildings resilient to wind environments using CFD models.

A Micro-Mechanics Based Corrosion Model for the Prediction of Service Life in Reinforced Concrete Structures

  • Song, Ha-Won;Kim, Ho-Jin;Kim, Tae-Hwan;Byun, Keun-Joo;Lee, Seung-Hoon
    • Corrosion Science and Technology
    • /
    • v.4 no.3
    • /
    • pp.100-107
    • /
    • 2005
  • Reinforcing steel bars in reinforced concrete structures are protected from corrosion by passive film on the steel surface inside concrete with high alkalinity. However, when the passive film breaks down due to chloride ion ingressed into the RC structures, a corrosion initiates at the surface of steel bars. Then, internal pressure by volume expansion of corrosion products in reinforcing bars induces cracking and spalling of cover concrete, which reduces not only durability performance but also structural performance in RC structures. In this paper, a service life prediction of RC structures is carried out by using a micro-mechanics based corrosion model. The corrosion model is composed of a chloride penetration model to evaluate the initiation of corrosion and an electric corrosion cell model and an oxygen diffusion model to evaluate the rate and the accumulated amounts of corrosion. Then, a corrosion cracking model is combined to the models to evaluate critical amount of corrosion product for initiation cracking in cover concrete. By implementing the models into a finite element analysis program, a time and space dependent corrosion analysis and a service life prediction of RC structures due to chloride attack are simulated and the results of the analysis are compared with test results. The effect of crack width on the corrosion and the service life of the RC structures are analyzed and discussed.

Robust 3D Model Hashing Scheme Based on Shape Feature Descriptor (형상 특징자 기반 강인성 3D 모델 해싱 기법)

  • Lee, Suk-Hwan;Kwon, Seong-Geun;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
    • /
    • v.14 no.6
    • /
    • pp.742-751
    • /
    • 2011
  • This paper presents a robust 3D model hashing dependent on key and parameter by using heat kernel signature (HKS), which is special shape feature descriptor, In the proposed hashing, we calculate HKS coefficients of local and global time scales from eigenvalue and eigenvector of Mesh Laplace operator and cluster pairs of HKS coefficients to 2D square cells and calculate feature coefficients by the distance weights of pairs of HKS coefficients on each cell. Then we generate the binary hash through binarizing the intermediate hash that is the combination of the feature coefficients and the random coefficients. In our experiment, we evaluated the robustness against geometrical and topological attacks and the uniqueness of key and model and also evaluated the model space by estimating the attack intensity that can authenticate 3D model. Experimental results verified that the proposed scheme has more the improved performance than the conventional hashing on the robustness, uniqueness, model space.