• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.374-386
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• 2022

Nowadays, research in deep learning leveraged automated computing and networking paradigm evidenced rapid contributions in terms of Software Defined Networking (SDN) and its diverse security applications while handling cybercrimes. SDN plays a vital role in sniffing information related to network usage in large-scale data centers that simultaneously support an improved algorithm design for automated detection of network intrusions. Despite its security protocols, SDN is considered contradictory towards DDoS attacks (Distributed Denial of Service). Several research studies developed machine learning-based network intrusion detection systems addressing detection and mitigation of DDoS attacks in SDN-based networks due to dynamic changes in various features and behavioral patterns. Addressing this problem, this research study focuses on effectively designing a multistage hybrid and intelligent deep learning classifier based on modified deep forest classification to detect DDoS attacks in SDN networks. Experimental results depict that the performance accuracy of the proposed classifier is improved when evaluated with standard parameters.

• Journal of Mechanical Science and Technology
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• 제18권8호
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• pp.1375-1387
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• 2004

A solution is given for the elastodynamic problem of a crack perpendicular to the graded interfacial zone in bonded materials under the action of anti plane shear impact. The interfacial zone is modeled as a nonhomogeneous interlayer with the power-law variations of its shear modulus and mass density between the two dissimilar, homogeneous half-planes. Laplace and Fourier integral transforms are employed to reduce the transient problem to the solution of a Cauchy-type singular integral equation in the Laplace transform domain. Via the numerical inversion of the Laplace transforms, the values of the dynamic stress intensity factors are obtained as a function of time. As a result, the influences of material and geometric parameters of the bonded media on the overshoot characteristics of the dynamic stress intensities are discussed. A comparison is also made with the corresponding elastostatic solutions, addressing the inertia effect on the dynamic load transfer to the crack tips for various combinations of the physical properties.

• Smart Structures and Systems
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• 제26권5호
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• pp.591-603
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• 2020

Dynamic deflection monitoring is an essential and critical part of structural health monitoring for high-speed railway bridges. Two critical problems need to be addressed when using inclinometer sensors for such applications. These include constructing a general representation model of inclination-deflection and addressing the ill-posed inverse problem to obtain the accurate dynamic deflection. This paper provides a dynamic deflection monitoring method with the placement of optimal inclinometer sensors for high-speed railway bridges. The deflection shapes are reconstructed using the inclination-deflection transformation model based on the differential relationship between the inclination and displacement mode shape matrix. The proposed optimal sensor configuration can be used to select inclination-deflection transformation models that meet the required accuracy and stability from all possible sensor locations. In this study, the condition number and information entropy are employed to measure the ill-condition of the selected mode shape matrix and evaluate the prediction performance of different sensor configurations. The particle swarm optimization algorithm, genetic algorithm, and artificial fish swarm algorithm are used to optimize the sensor position placement. Numerical simulation and experimental validation results of a 5-span high-speed railway bridge show that the reconstructed deflection shapes agree well with those of the real bridge.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 가을 학술발표논문집 Vol.31 No.2 (3)
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• pp.268-270
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• 2004

센서 네트워크는 제한된 메모리와 배터리를 가진 센서 노드로 구성되는 네트워크로서, 노드의 이동이나 장애로 인한 토폴로지 변화가 빈번하다. 이러한 센서 노드의 주소 할당에 있어서 기존의 방식들은 고정 주소를 할당하는 방식이므로 네트워크의 구성형태나 토폴로지의 변화에 맞게 주소를 변경하기 어렵다는 문제점이 있다. 이에 본 논문에서는 트리 기반의 동적 주소 할당 방식을 제안하였는데, 이는 초기에 트리 기반으로 생성된 노드 주소를 동적으로 할당하여, 라우팅 경로 등의 네트워크 변화에 따라 유동적으로 주소를 재할당한다. 메커니즘의 검증을 위해서는 ns-2 시뮬레이터를 사용하여 동작을 할인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권12호
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• pp.3398-3415
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• 2023

Internet-of-Things (IoT) is an emerging technology that interconnects millions of small devices to enable communication between the devices. It is heavily deployed across small scale to large scale industries because of its wide range of applications. These devices are very capable of transferring data over the internet including critical data in few applications. Such data is exposed to various security threats and thereby raises privacy-related concerns. Even devices can be compromised by the attacker. Modern cryptographic algorithms running on traditional machines provide authentication, confidentiality, integrity, and non-repudiation in an easy manner. IoT devices have numerous constraints related to memory, storage, processors, operating systems and power. Researchers have proposed several hardware and software implementations for addressing security attacks in lightweight encryption mechanism. Several works have made on lightweight block ciphers for improving the confidentiality by means of providing security level against cryptanalysis techniques. With the advances in the cipher breaking techniques, it is important to increase the security level to much higher. This paper, focuses on securing the critical data that is being transmitted over the internet by PRESENT using key-based dynamic S-Box. Security analysis of the proposed algorithm against other lightweight block cipher shows a significant improvement against linear and differential attacks, biclique attack and avalanche effect. A novel key-based dynamic S-Box approach for PRESENT strongly withstands cryptanalytic attacks in the IoT Network.

• 조명전기설비학회논문지
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• 제19권8호
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• pp.13-18
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• 2005

본 연구는 스캔 구동 회로의 변화에 따른 교류형 플라즈마 표시기의 구동 특성에 관한 것이다. 본 연구에서는 교류형 플라즈마 표시기의 용량성 부하 특성을 활용하여 스캔 라인 당 소요되는 스위치의 수를 줄일 수 있는 회로를 제안하고 그 적용 가능성을 고찰하였다. 제안된 방식의 실용화 가능성에 대한 검증을 위하여 방전 유지 전압의 변화에 따라 어드레싱 전압의 변화를 관찰하여 동적 전압 마진을 측정한 결과, 기존 방식에 비하여 9[V] 가량의 전압마진 감소가 관찰되었다. 이는 제안된 방식의 경우 선택된 전극의 스캔 기간에 이웃한 전극에 전위에 영향을 줌으로써 상호 간섭이 유발되는 효과에 의한 것으로 해석되었다. 최소 어드레싱 전압과 어드레싱 방전의 방전 지연 시간에 변화가 없는 점을 감안하면 제안된 방식의 실제 회로 적용은 가능할 것으로 사료된다.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2005년도 International Meeting on Information Displayvol.II
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• pp.1269-1272
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• 2005

We propose a simple and efficient driving algorithm to reduce Dynamic False Contour(DFC) in Plasma Display Panels(PDPs) by using both accumulation and combination of light emission periods. Although the accumulative way of light emission in sustain period is regarded as more effective than combinational way to reduce DFC, it takes much addressing time to express high gray-scale. Therefore, we combine accumulative and combinational light emission methods to reduce DFC. In the proposed method, one TV field (16.7ms) is composed of four combinational subfields for expressing small gray scales and fifteen accumulative subfields for large gray scales. In addition, we use some Graphic Signal Processing(GSP) algorithm to get more natural images by reducing DFC.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.493-502
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• 2020

Traditionally, road projects are initiated based on an assessment of their economic benefit, after which the environmental, social and governance effects are addressed discretely for the project according to a set of predetermined alternatives. Sustainable road infrastructure planning is vital as issues like diminishing access to road construction supplies, water scarcity, Greenhouse Gas emissions, road-related fatalities and congestion pricing etc., have imposed severe economic, social, and environmental damages to the society. In the process of addressing these sustainability factors in the operational phase of the project, the dynamics of these factors are generally ignored. This paper argues that effective delivery of sustainable roads should consider such dynamics and highlights how different aspects of sustainability have the potential to affect project sustainability. The paper initially presents the different sustainability-assessment tools that have been developed to determine the sustainability performance of road projects and discuss the inability of these tools to model the interrelationships among sustainability-related factors. The paper then argues the need for a new assessment framework that facilitates modelling these dynamics at the macro-level (system level) and helping policymakers for sustainable infrastructure planning through evaluating regulatory policies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.538-561
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• 2020

Recommender Systems (RecSys) have a major role in e-commerce for recommending products, which they may like for every user and thus improve their business aspects. Although many types of RecSyss are there in the research field, the state of the art RecSys has focused on finding the user similarity based on sequence (e.g. purchase history, movie-watching history) analyzing and prediction techniques like Recurrent Neural Network in Deep learning. That is RecSys has considered as a sequence prediction problem. However, evaluation of similarities among the customers is challenging while considering temporal aspects, context and multi-component ratings of the item-records in the customer sequences. For addressing this issue, we are proposing a Deep Learning based model which learns customer similarity directly from the sequence to sequence similarity as well as item to item similarity by considering all features of the item, contexts, and rating components using Dynamic Temporal Warping(DTW) distance measure for dynamic temporal matching and 2D-GRU (Two Dimensional-Gated Recurrent Unit) architecture. This will overcome the limitation of non-linearity in the time dimension while measuring the similarity, and the find patterns more accurately and speedily from temporal and spatial contexts. Experiment on the real world movie data set LDOS-CoMoDa demonstrates the efficacy and promising utility of the proposed personalized RecSys architecture.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권4호
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• pp.385-398
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• 2009

This paper aims to find a suitable solution to joint allocation of sub-channel and transmit power for multiple users in an IEEE 802.16e OFDMA/TDD cellular system. We propose the FASA (Fairness insured Aggressive Sub-channel Allocation) algorithm, which is a dynamic channel allocation algorithm that considers all of the users' channel state information conditionally in order to maximize throughput while taking into account fairness. A dynamic power allocation algorithm, i.e., an improved CHC algorithm, is also proposed in combination with the FASA algorithm. It collects the extra downlink transmit power and re-allocates it to other potential users. Simulation results show that the joint allocation scheme with the improved CHC power allocation algorithm provides an additional increase of sector throughput while simultaneously enhancing fairness. Four frames of time delay for CQI feedback and scheduling are considered. Furthermore, by addressing the difference between uplink and downlink scheduling in an IEEE 802.16e OFDMA TDD system, we can employ the uplink channel information directly via channel sounding, resulting in more accurate uplink dynamic resource allocation.