• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.35-46
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• 2017

Recently, attackers using malicious code in cyber security have been increased by attaching malicious code to a mail and inducing the user to execute it. Especially, it is dangerous because it is easy to execute by attaching a document type file. The author analysis is a research area that is being studied in NLP (Neutral Language Process) and text mining, and it studies methods of analyzing authors by analyzing text sentences, texts, and documents in a specific language. In case of attack mail, it is created by the attacker. Therefore, by analyzing the contents of the mail and the attached document file and identifying the corresponding author, it is possible to discover more distinctive features from the normal mail and improve the detection accuracy. In this pager, we proposed IADA2(Intelligent Attack mail Detection based on Authorship Analysis) model for attack mail detection. The feature vector that can classify and detect attack mail from the features used in the existing machine learning based spam detection model and the features used in the author analysis of the document and the IADA2 detection model. We have improved the detection models of attack mails by simply detecting term features and extracted features that reflect the sequence characteristics of words by applying n-grams. Result of experiment show that the proposed method improves performance according to feature combinations, feature selection techniques, and appropriate models.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.5
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• pp.875-884
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• 2024

The proliferation of IoT networks has led to an increase in cyber attacks, highlighting the importance of Network Intrusion Detection Systems (NIDS). To overcome the limitations of traditional NIDS and cope with more sophisticated cyber attacks, there is a trend towards integrating artificial intelligence models into NIDS. However, AI-based NIDS are vulnerable to adversarial attacks, which exploit the weaknesses of algorithm. Model Type Inference Attack is one of the types of attacks that infer information inside the model. This paper proposes an optimized framework for Model Type Inference attacks against NIDS models, applying more realistic assumptions. The proposed method successfully trained an attack model to infer the type of NIDS models with an accuracy of approximately 0.92, presenting a new security threat to AI-based NIDS and emphasizing the importance of developing defence method against such attacks.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.1
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• pp.1-7
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• 2023

Convolutional neural networks have already been applied to various fields beyond human visual processing capabilities in the image processing area. However, they are exposed to a severe risk of deteriorating model performance due to the appearance of adversarial attacks. In addition, defense technology to respond to adversarial attacks is effective against the attack but is vulnerable to other types of attacks. Therefore, to respond to an adversarial attack, it is necessary to analyze how the performance of the adversarial attack deteriorates through the process inside the convolutional neural network. In this study, the adversarial attack of the Alexnet and VGG11 models was analyzed using the population sparseness index, a measure of neuronal activity in neurophysiology. Through the research, it was observed in each layer that the population sparsity index for adversarial examples showed differences from that of benign examples.

• Convergence Security Journal
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• v.21 no.3
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• pp.49-56
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• 2021

Recently, artificial intelligence is regarded as an essential technology in our society. In particular, the invasion of privacy in artificial intelligence has become a serious problem in modern society. Split learning, proposed at MIT in 2019 for privacy protection, is a type of federated learning technique that does not share any raw data. In this study, we studied a safe and accurate segmentation learning model using known differential privacy to safely manage data. In addition, we trained SVHN and GTSRB on a split learning model to which 15 different types of differential privacy are applied, and checked whether the learning is stable. By conducting a learning data extraction attack, a differential privacy budget that prevents attacks is quantitatively derived through MSE.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.3
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• pp.231-238
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• 2002

In this paper, we present a new approach to autopilot design for skid-to-turn missiles which may have severe aerodynamic cross-couplings and nonlinearities with angle of attack. The model of missile motion is derived in the maneuver plane and, based on that model, pitch, yaw, and roll autopilot are designed. They are composed of a nonlinear term which compensates for the aerodynamic couplings and nonlinearities and a linear controller driven by the measured outputs of missile accelerations and angular rates. Besides the outputs, further information such as Mach number, dynamic pressure, total angle of attack, and bank angle is required. With the proposed autopilot and simple estimators of bank angle and total angle of attack, it is shown by computer simulations that the induced moments and some aerodynamic nonlinearities are properly compensated and that the performance is superior to that of the conventional ones.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.159-176
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• 1991

The probability of target survival is the most important factor in the target assignment, Most of the studies about it have assumed the case of one target and ane weapon type. Therefore, they can not be applied to the real situation. In this paper. the quantity and type of enemy assets of the friendly force are considered simultaneously. Considered defense type is the coordinated defense with no impact point prediction. The objective function is to minimize the expected total survival value of targets which are scattered in the defense area. The rules of aircraft assignment are as follows : first, classify targets into several groups, each of those has the same desired damage level secondly. select the critical group which has the least survival value in accordance with the additional aircraft assignment, and finally. assign the same number of attack assets against each target in the critical group. In this paper, the attack assets, the escort assets, and the defense assets are considered. The model is useful to not only the simple aircraft assignment problem but also the complicated wargame models.

• Journal of computational fluids engineering
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• v.1 no.1
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• pp.98-111
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• 1996

The compressible laminar and turbulent viscous flows on a slender body in supersonic speed as well as subsonic speed have been numerically simulated at high angle of attack. The steady and time-accurate compressible thin-layer Navier-Stokes code based on an implicit upwind-biased LU-SGS algorithm has been developed and specifically applied at angles of attack of 20, 30 and 40 dog, respectively. The modified eddy-viscosity turbulence model suggested by Degani and Schiff was used to simulate the case of turbulent flow. Any geometric asymmetry and numerical perturbation have not been intentionally or artificially imposed in the process of computation. The purely numerical results for laminar and turbulent cases, however, show clear asymmetric formation of vortices which were observed experimentally. Contrary to the subsonic results, the supersonic case shows the symmetric formation of vortices as indicated by the earlier experiments.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.589-594
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• 2007

This paper is shown new method for durability assesment and design have been noticed to be very valuable has been successfully applied to predict concrete structures. This paper provides that a new approach for predicting the corrosion durability of reinforced concrete structures exposed to chloride attack. In this method, the prediction can be updated successive1y by the Bayesian theory when additional data are available. The stochastic properties of model parameters are explicitly taken into account into the model the probability of the durability limit is determined from the samples obtained from the Latin hypercube sampling technique. The new method may be very useful in designing important concrete structures and help to predict the remaining service life of existing concrete structures under chloride attack environments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.258-261
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• 2002

최근 네트워크 취약점 검색 방법을 이용한 침입 공격이 증가하는 추세이며 이런 공격에 대하여 적절하게 실시간 탐지 및 대응 처리하는 침입방지시스템(IPS: Intrusion Prevention System)에 대한 연구가 지속적으로 이루어지고 있다. 본 논문에서는 시스템에 허락을 얻지 않은 서비스거부 공격(Denial of Service Attack) 기술 중 TCP의 신뢰성 및 연결 지향적 전송서비스로 종단간에 이루어지는 3-Way Handshake를 이용한 Syn Flooding Attack에 대하여 침입시도패킷 정보를 수집, 분석하고 퍼지인식도(FCM : Fuzzy Cognitive Maps)를 이용한 침입시도여부결정 및 대응 처리하는 네트워크 기반의 실시간 탐지 및 방지 모델(Network based Real Time Scan Detection & Prevention Model)을 제안한다.

• Annual Conference of KIPS
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• 2002.11a
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• pp.363-366
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• 2002

최근 네트워크 취약점 검색 방법을 이용한 침입 공격이 늘어나는 추세이며 이런 공격에 대하여 적절하게 실시간 탐지 및 대응 처리하는 침입방지시스템(IPS: Intrusion Prevention System)에 대한 연구가 지속적으로 이루어지고 있다. 본 논문에서는 시스템에 허락을 얻지 않은 서비스 거부 공격(Denial of Service Attack) 기술 중 TCP의 신뢰성 및 연결 지향적 전송서비스로 종단간에 이루어지는 3-Way Handshake를 이용한 Syn Flooding Attack에 대하여 침입시도패킷 정보를 수집, 분석하고 퍼지인식도(FCM : Fuzzy Cognitive Maps)를 이용한 침입시도여부를 결정하는 네트워크 기반의 실시간 탐지 모델(Network based Real Time Scan Detection Model)을 제안한다.