• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1109-1122
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• 2016

Certificateless public key cryptography is a technique that can solve the certificate management problem of a public key cryptosystem and clear the key escrow issue of ID-based cryptography using the public key in user ID. Although the studies were actively in progress, many existing schemes have been designed without taking into account the safety of the secret value with the decryption key exposure attacks. If previous secret values and decryption keys are exposed after replacing public key, a valid private key can be calculated by obtaining the partial private key corresponding to user's ID. In this paper, we propose a new security model which ensures the security against the key exposure attacks and show that several certificateless public key encryption schemes are insecure in the proposed security model. In addition, we design a certificateless public key encryption scheme to be secure in the proposed security model and prove it based on the DBDH(Decisional Bilinear Diffie-Hellman) assumption.

• Journal of Korea Multimedia Society
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• v.23 no.5
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• pp.641-649
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• 2020

As the usage of mobile devices extremely increases, malicious mobile apps(applications) that target mobile users are also increasing. It is challenging to detect these malicious apps using traditional malware detection techniques due to intelligence of today's attack mechanisms. Deep learning (DL) is an alternative technique of traditional signature and rule-based anomaly detection techniques and thus have actively been used in numerous recent studies on malware detection. In order to develop DL-based defense mechanisms against intelligent malicious apps, feeding recent datasets into DL models is important. In this paper, we develop a DL-based model for detecting intelligent malicious apps using KU-CISC 2018-Android, the most up-to-date dataset consisting of benign and malicious Android apps. This dataset has hardly been addressed in other studies so far. We extract OPcode sequences from the Android apps and preprocess the OPcode sequences using an N-gram model. We then feed the preprocessed data into LSTM and apply the concept of Information Gain to improve performance of detecting malicious apps. Furthermore, we evaluate our model with numerous scenarios in order to verify the model's design and performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.7
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• pp.647-654
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• 2010

In this study, an efficient ornithopter aerodynamic model, which is applicable to ornithopter wing design considering fluid-structure interaction or ornithopter flight dynamics and control simulation, was proposed and experimentally validated through the wind tunnel experiments. Due to the ornithopter aerodynamics governed by unsteady low Reynolds number flow, an experimental device was specially designed and developed. A part of the experimental device, 2-axis loadcell, was situated in the non-inertial frame; the dynamic calibration method was established to compensate the inertial load for pure aerodynamic load measurements. The characteristics of proposed aerodynamic model were compared with the experimental data in terms of mean and root-mean-square values of lift and drag coefficients with respect to the flow speed, flapping frequency, and fixed angle of attack.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.293-302
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• 2015

With the attack information collected during SMS phishing investigation, this paper will propose SMS phishing profiling model applying criminal profiling. Law enforcement agencies have used signature analysis by apk file hash and analysis of C&C IP address inserted in the malware. However, recently law enforcement agencies are facing the challenges such as signature diversification or code obfuscation. In order to overcome these problems, this paper examined 169 criminal cases and found out that 89% of serial number in cert.rsa and 80% of permission file was reused in different cases. Therefore, the proposed SMS phishing profiling model is mainly based on signature serial number and permission file hash. In addition, this model complements the conventional file hash clustering method and uses code similarity verification to ensure reliability.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.4
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• pp.16-22
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• 2012

In this paper, the forensic marking algorithm is proposed using psychoacoustic model II and MDCT for high-quality audio. The proposed forensic marking method, that inserts the user fingerprinting code of the audio content into the selected sub-band, in which audio signal energy is lower than the spectrum masking level. In the range of the one frame which has 2,048 samples for FFT of original audio signal, the audio forensic marking is processed in 3 sub-bands. According to the average attack of the fingerprinting codes, one frame's SNR is measured on 100% trace ratio of the collusion codes. When the lower strength 0.1 of the inserted fingerprinting code, SNR is 38.44dB. And in case, the added strength 0.5 of white gaussian noise, SNR is 19.09dB. As a result, it confirms that the proposed audio forensic marking algorithm is maintained the marking robustness of the fingerprinting code and the audio high-quality.

• Wind and Structures
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• v.17 no.6
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• pp.647-670
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• 2013

The paper presents a numerical approach to study of fluid flow characteristics and to predict performance of wind turbines. The numerical model is based on Finite-volume method (FVM) discretization of unsteady Reynolds-averaged Navier-Stokes (URANS) equations. The movement of turbine blades is modeled using moving mesh technique. The turbulence is modeled using commonly used turbulence models: Renormalization Group (RNG) k-${\varepsilon}$ turbulence model and the standard k-${\varepsilon}$ and k-${\omega}$ turbulence models. The model is validated with the experimental data over a large range of tip-speed to wind ratio (TSR) and blade pitch angles. In order to demonstrate the use of numerical method as a tool for designing wind turbines, two dimensional (2-D) and three-dimensional (3-D) simulations are carried out to study the flow through a small scale Darrieus type H-rotor Vertical Axis Wind Turbine (VAWT). The flows predictions are used to determine the performance of the turbine. The turbine consists of 3-symmetrical NACA0022 blades. A number of simulations are performed for a range of approaching angles and wind speeds. This numerical study highlights the concerns with the self-starting capabilities of the present VAWT turbine. However results also indicate that self-starting capabilities of the turbine can be increased when the mounted angle of attack of the blades is increased. The 2-D simulations using the presented model can successfully be used at preliminary stage of turbine design to compare performance of the turbine for different design and operating parameters, whereas 3-D studies are preferred for the final design.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.33-40
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• 2009

Ever since the network-based malicious code commonly known as a 'worm' surfaced in the early part of the 1980's, its prevalence has grown more and more. The RCS (Random Constant Spreading) worm has become a dominant, malicious virus in recent computer networking circles. The worm retards the availability of an overall network by exhausting resources such as CPU capacity, network peripherals and transfer bandwidth, causing damage to an uninfected system as well as an infected system. The generation and spreading cycle of these worms progress rapidly. The existing studies to counter malicious code have studied the Microscopic Model for detecting worm generation based on some specific pattern or sign of attack, thus preventing its spread by countering the worm directly on detection. However, due to zero-day threat actualization, rapid spreading of the RCS worm and reduction of survival time, securing a security model to ensure the survivability of the network became an urgent problem that the existing solution-oriented security measures did not address. This paper analyzes the recently studied efficient dynamic network. Essentially, this paper suggests a model that dynamically controls the RCS worm using the characteristics of Power-Law and depth distribution of the delivery node, which is commonly seen in preferential growth networks. Moreover, we suggest a model that dynamically controls the spread of the worm using information about the depth distribution of delivery. We also verified via simulation that the load for each node was minimized at an optimal depth to effectively restrain the spread of the worm.

• Wind and Structures
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• v.22 no.2
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• pp.161-184
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• 2016

Long-span suspension bridges have evolved through the years and with them, the bridge girder decks improved as well, changing their shapes from standard box-deck girders to twin box and multi-box decks sections. The aerodynamic characteristics of the new generation of twin and multiple-decks are investigated nowadays, to provide the best design wind speeds and the optimum dimensions such bridges could achieve. The multi-box Megane bridge deck is one of the new generation bridge decks, consisting of two side decks for traffic lanes and two middle decks for railways, linked between them with connecting beams. Three-dimensional CFD simulations were performed by employing the Large Eddy Simulation (LES) algorithm with a standard Smagorinsky subgrid-scale model, for $Re=9.3{\times}10^7$ and angles of attack ${\alpha}=-4^{\circ}$, $-2^{\circ}$, $0^{\circ}$, $2^{\circ}$ and $4^{\circ}$. Also, a wind tunnel experiment was performed for a scaled model, 1:80 of the Megane bridge deck section, for $Re=5.1{\times}10^5$ and the aerodynamic static coefficients were found to be in good agreement with the results obtained from the CFD-LES model. However the aerodynamic coefficients determined individually, from the CFD-LES model, for each of the traffic and railway decks of the Megane bridge, varied significantly, especially for the downstream traffic deck. Also the pressure distribution and the effect of the spacing between the connecting beams, on the wind speed profiles showed a slight increase in turbulence above the downstream traffic and railway decks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.455-464
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• 2020

With a variety of data types and high utilization of data, non-relational databases are a popular data storage because it supports better availability and scalability. The increasing use of this technology also brings the risk of NoSQL injection attacks. Existing works mostly discuss the rule-based detection of NoSQL injection attacks that it is hard to deal with NoSQL queries beyond the coverage of the rules. In this paper, we propose a model for detecting NoSQL injection attacks. Our model is based on deep learning algorithms that select features from NoSQL queries using CNN, and classify NoSQL queries using RNN. Also, we experiment the proposed model to compare with existing models, and find that our model outperforms traditional models in terms of detection rate.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.5
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• pp.861-868
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• 2010

As CAS, X-ATK, and INT models considered as the most typical Air-to-Ground operation models in ROKAF are mainly designed as the voice-centered system between aircraft and ground control facilities, it is critical to newly develop the Link-16 based model for the ROK-US combined operation between F-15K, AWACS, M-SAM, and KDX-III equipped with Link-16. Former studies had been limited to the CAS operation, and they had mainly focused on reducing the voice transmission time to exchange the information between each mission step with maintaining existing operation steps. Therefore, this paper makes up the weak point in former studies, thereby designing new Air-to-Ground operation model for CAS, X-ATK, INT mission using Enterprise Architecture OV6c, which enables both aircraft and ground control facilities or between aircraft to obtain the real-time information on the location, identification, armament and the real-time image data through the broadcasting function. Based on the analysis of new operation model, we come to a conclusion that by simultaneously exchanging the information on mission between nodes concerned through the broadcasting function of Link-16. It is possible to cut down superfluous steps among the mission steps, and to reduce the mission time. It is clear that it gives rise to improve the battle efficiency and the decision-making tempo as well as the battlefield situational awareness.