• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.1
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• pp.57-65
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• 2016

Threat evaluation is a process to estimate the threat score which enemy aerial threat poses to defended assets. The objective of threat evaluation is concerned with making an engagement priority list for optimal weapon allocation. Traditionally, the threat evaluation of massive air threats has been carried out by air defence experts, but the human decision making is less effective in real aerial attack situations with massive enemy fighters. Therefore, automation to enhance the speed and efficiency of the human operation is required. The automatic threat evaluation by air defense experts who will perform multi-variable judgment needs formal models to accurately quantify their linguistic evaluation of threat level. In this paper we propose a threat evaluation model by using a fuzzy rule-based inference method. Fuzzy inference is an appropriate method for quantifying threat level and integrating various threat attribute information. The performance of the model has been tested with a simulation that reflected real air threat situation and it has been verified that the proposed model was better than two conventional threat evaluation models.

• Convergence Security Journal
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• v.18 no.2
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• pp.19-24
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• 2018

In this study, for evaluating the cyber threat, we presented a quantitative assessment measures of the threat-level with multiple factors. The model presented in the study is a compound model with the 4 factors; the attack method, the actor, the strength according to the type of the threat, and the proximity to the target. And the threat-level can be quantitatively evaluated with the Fuzzy Inference. The model will take the information in natural language and present the threat-level with quantified data. Therefore an organization can accurately evaluate the cyber threat-level and take it into account for judging threat.

• Journal of the Korea Institute of Military Science and Technology
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• v.11 no.1
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• pp.93-101
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• 2008

It is difficult for a MWR(Missile Warning Radar) to perform a threat decision accurately since there is no tracking part which gives more accurate threat information to the MWR. In this paper, the threat decision algorithm is proposed using an azimuth angular rate to improve the accuracy. The azimuth angular rate is dependent upon the direction of an approaching target. The target is classified into a threat or non-threat using a boundary condition of the azimuth angular rate. The boundary condition is determined using the Monte-Carlo simulation. The performance of the proposed algorithm is evaluated using this condition at field tests of MWR. The efficiency of the proposed method for the threat decision is proved by comparing the results of field tests with the simulation results.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.35-49
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• 2009

In electronic warfare settings, battlefield helicopters identify various threats based upon threat data, which are acquired using their multi-sensors of aircraft survivability equipment (ASE). To continually function despite of potential threats and successfully execute their missions, the battlefield helicopters have to repeatedly report threats in simulated battlefield situations. Toward this ends, the paper presents threat unification using multi-sensor simulator and its implementation. The simulator consists of (1) threat attributes generator, which models threats against battlefield helicopters and defines their specific attributes, (2) threat data generator, which generates threats, being similar to real ones, using normal, uniform, and exponential distributions, and (3) graphic display for threat analysis and unification, which shows unified threat information, for example, threat angle and its level. We implement a multi-sensor threat simulator that can be repeatedly operable in various simulated battlefield settings. Further, we report experimental results that, in addition to tangibly modeling the threats to battlefield helicopters, test the capabilities of threat unification using our simulator.

• Journal of Platform Technology
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• v.11 no.2
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• pp.15-25
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• 2023

This study analyzes the limitations of the insider threat datasets used for insider threat detection research and compares and analyzes the solution-based insider threat data with public insider threat data using a security solution to overcome this. Through this, we design a data format suitable for insider threat detection and implement a system that can safely share insider threat information between different institutions and companies using blockchain technology. Currently, there is no dataset collected based on actual events in the insider threat dataset that is revealed to researchers. Public datasets are virtual synthetic data randomly created for research, and when used as a learning model, there are many limitations in the real environment. In this study, to improve these limitations, a private blockchain was designed to secure information sharing between institutions of different affiliations, and a method was derived to increase reliability and maintain information integrity and consistency through agreement and verification among participants. The proposed method is expected to collect data through an outflow threat collector and collect quality data sets that posed a threat, not synthetic data, through a blockchain-based sharing system, to solve the current outflow threat dataset problem and contribute to the insider threat detection model in the future.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.474-481
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• 2011

The Electronic Warfare Computer for the Aircraft Survivability Equipment will improve the ability for countermeasures by analysis about threat information. This paper suggests method that threat data integration of multiple sensors(Radar Warning Receiver, Laser Warning Receiver, Missile Warning Receiver). The algorithm of threat data integration is based on detected threat sequence and azimuth information. The threat sequence information is analyzed in advance and the azimuth data is received from sensors. The suggested method is evaluated through simulation under the environment like real helicopter.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.2
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• pp.236-243
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• 2016

This paper presents a threat list acquisition method in an engagement area using the support vector machines (SVM). The proposed method consists of track creation, track estimation, track feature extraction, and threat list classification. To classify the threat track robustly, dynamic track estimation and pattern recognition algorithms are used. Dynamic tracks are estimated accurately by approximating a track movement using position, velocity and time. After track estimation, track features are extracted from the track information, and used to classify threat list. Experimental results showed that the threat list acquisition method in the engagement area achieved about 95 % accuracy rate for whole test tracks when using the SVM classifier. In case of improving the real-time process through further studies, it can be expected to apply the fire control systems.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.6
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• pp.797-805
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• 2019

Threats targeting cyberspace are becoming more intelligent and increasing day by day. To cope with such cyber threats, it is essential to improve the coping ability of system security officers. In this paper, we propose a simulated threat generator that automatically generates cyber threats for cyber defense training. The proposed Simulated Threat Generator is designed with MITRE ATT & CK(Adversarial Tactics, Techniques and Common Knowledge) framework to easily add an evolving cyber threat and select the next threat based on the threat execution result.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.807-816
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• 2018

Threat hunting is defined as a process of proactively and iteratively searching through networks to detect and isolate advanced threats that evade existing security solutions. The main concept of threat hunting is to find out weak points and remedy them before actual cyber threat has occurred. And HMM(Hunting Maturity Matrix) is suggested to evolve hunting processes with five levels, therefore, CSOC(Cyber Security Operations Center) can refer HMM how to make them safer from complicated and organized cyber attacks. We are developing a system for cyber situation awareness system with pro-active threat hunting process called unMazeTM. With this unMaze, it can be upgraded CSOC's HMM level from initial level to basic level. CSOC with unMaze do threat hunting process not only detecting existing cyber equipment post-actively, but also proactively detecting cyber threat by fusing and analyzing cyber asset data and threat intelligence.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.43-52
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• 2021

In weapon assignment studies to defend against threats such as ballistic missiles and long range artillery, threat assessment was partially lacking in analysis of various threat attributes, and considering the threat characteristics of warheads, which are difficult to judge in the early flight stages, it is very important to apply more reliable optimal solutions than approximate solution using LP model, Meta heuristics Genetic Algorithm, Tabu search and Particle swarm optimization etc. Our studies suggest Generic Rule based threat evaluation and weapon assignment algorithm in the basis of various attributes of threats. First job of studies analyzes information on Various attributes such as the type of target, Flight trajectory and flight time, range and intercept altitude of the intercept system, etc. Second job of studies propose Rule based threat evaluation and weapon assignment algorithm were applied to obtain a more reliable solution by reflection the importance of the interception system. It analyzes ballistic missiles and long-range artillery was assigned to multiple intercept system by real time threat assessment reflecting various threat information. The results of this study are provided reliable solution for Weapon Assignment problem as well as considered to be applicable to establishing a missile and long range artillery defense system.