• 제목/요약/키워드: Network Evolution

검색결과 643건 처리시간 0.024초

하드웨어 기반 Anti-DDoS 대응 장비 고속 패킷 필터링을 위한 Hi-DPI 알고리즘 연구 (Development Hi-DPI Algorithm for High Speed Packet Filtering of Anti-DDoS based on HW)

  • 김점구
    • 융합보안논문지
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    • 제17권2호
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    • pp.41-51
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    • 2017
  • 인터넷 활용 범위의 폭발적인 증가는 점차적으로 네트워크 속도와 용량을 초고속화 하고 대용량화로 빠르게 진화해 가고 있다. 이에 따라 스위치 라우터 등 네트워크 장비들은 하드웨어에 기반 한 빠른 기술 진화로 대처를 하고 있으나 초연결사회에 가장 기본적이고 필수적인 네트워크 보안시스템의 기술 진화는 수만 가지의 보안 이슈와 시그니처(signature)에 대해서 수시 변경과 갱신을 필요로 하기 때문에 소프트웨어에 기반 한 기술적인 한계를 극복하기가 쉽지 않다. 본 논문은 이와 같은 DDoS 대응 장비를 설치 운영할 때의 패킷 필터링 속도 저하 문제점을 개선하고자 FPGA(Field Programmable Gate Array)의 하드웨어적인 특성과 병렬처리 특성을 최대한 반영한 DPI 알고리즘인 Hi-DPI를 제안하고 실용성을 검증하고자 한다.

액티브 네트워크에서의 연합을 통한 보안 관리 (Security Management by Zone Combination in Active Networks)

  • 장범환;김동수;권윤주;남택용;정태명
    • 한국정보과학회논문지:정보통신
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    • 제30권1호
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    • pp.82-96
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    • 2003
  • 인터넷은 개방 프로토콜의 영향으로 빠르게 성장하여 글로벌 네트워크 환경으로 진화하였지만, 많은 위협들로부터 자산을 보호해야하는 문제를 초래하게 되었다. 정보보호에 있어서, 조직 내 전체 보안시스템들을 완전 가동하여 사고 발생 이전에 침입을 차단하는 것은 최선책이지만, 사고 발생 이전 또는 새롭게 개발된 공격들을 차단하기는 대단히 어렵다. 보안연합은 신뢰할 수 있는 보안영역들간의 신속하고 정확한 보안 정보 교환과 긴밀한 강호 협력을 통해 잠재적인 공격들을 사전에 준비하여 대응할 수 있으며 새로운 보호 기능들을 능동적으로 갱신하여 보다 강력한 보안 기능과 신속하게 대응한 수 있는 구조이다.

Prioritization-Based Model for Effective Adoption of Mobile Refactoring Techniques

  • Alhubaishy, Abdulaziz
    • International Journal of Computer Science & Network Security
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    • 제21권12spc호
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    • pp.375-382
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    • 2021
  • The paper introduces a model for evaluating and prioritizing mobile quality attributes and refactoring techniques through the examination of their effectiveness during the mobile application development process. The astonishing evolution of software and hardware has increased the demand for techniques and best practices to overcome the many challenges related to mobile devices, such as those concerning device storage, network bandwidth, and energy consumption. A number of studies have investigated the influence of refactoring, leading to the enhancement of mobile applications and the overcoming of code issues as well as hardware issues. Furthermore, rapid and continuous mobile developments make it necessary for teams to apply effective techniques to produce reliable mobile applications and reduce time to market. Thus, we investigated the influence of various refactoring techniques on mobile applications to understand their effectiveness in terms of quality attributes. First, we extracted the most important mobile refactoring techniques and a set of quality attributes from the literature. Then, mobile application developers from nine mobile application teams were recruited to evaluate and prioritize these quality attributes and refactoring techniques for their projects. A prioritization-based model is examined that integrates the lightweight multi-criteria decision making method, called the best-worst method, with the process of refactoring within mobile applications. The results prove the applicability and suitability of adopting the model for the mobile development process in order to expedite application production while using well-defined procedures to select the best refactoring techniques. Finally, a variety of quality attributes are shown to be influenced by the adoption of various refactoring techniques.

Apply Blockchain to Overcome Wi-Fi Vulnerabilities

  • Kim, Seong-Kyu (Steve)
    • Journal of Multimedia Information System
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    • 제6권3호
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    • pp.139-146
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    • 2019
  • This paper, wireless internet such as Wi-Fi has a vulnerability to security. Blockchain also means a 'Ledger' in which transaction information that occurs on a public or private network is encrypted and shared among the network participants. Blockchain maintains information integrity by making it impossible for a particular node to tamper with information arbitrarily, a feature that would result in changes in the overall blockchain hash value if any one transaction information that constitutes a block was changed. The complete sharing of information through a peer-to-peer network will also cripple hacking attempts from outside, targeting specialized nodes, and prepare for the "single point of failure" risk of the entire system being shut down. Due to the value of these Blockchain, various types of Blockchain are emerging, and related technology development efforts are also actively underway. Various business models such as public block chains such as Bitcoin, as well as private block chains that allow only certain authorized nodes to participate, or consortium block chains operated by a select few licensed groups, are being utilized. In terms of technological evolution, Blockchain also shows the potential to grow beyond cryptocurrency into an online platform that allows all kinds of transactions with the advent of 'Smart Contract'. By using Blockchain technology, the company makes suggestions to overcome the vulnerability of wireless Internet.

Evolutionary Computing Driven Extreme Learning Machine for Objected Oriented Software Aging Prediction

  • Ahamad, Shahanawaj
    • International Journal of Computer Science & Network Security
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    • 제22권2호
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    • pp.232-240
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    • 2022
  • To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

Quadrilateral Irregular Network for Mesh-Based Interpolation

  • Tae Beom Kim;Chihyung Lee
    • 지질공학
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    • 제33권3호
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    • pp.439-459
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    • 2023
  • Numerical analysis has been adopted in nearly all modern scientific and engineering fields due to the rapid and ongoing evolution of computational technology, with the number of grid or mesh points in a given data field also increasing. Some values must be extracted from large data fields to evaluate and supplement numerical analysis results and observational data, thereby highlighting the need for a fast and effective interpolation approach. The quadrilateral irregular network (QIN) proposed in this study is a fast and reliable interpolation method that is capable of sufficiently satisfying these demands. A comparative sensitivity analysis is first performed using known test functions to assess the accuracy and computational requirements of QIN relative to conventional interpolation methods. These same interpolation methods are then employed to produce simple numerical model results for a real-world comparison. Unlike conventional interpolation methods, QIN can obtain reliable results with a guaranteed degree of accuracy since there is no need to determine the optimal parameter values. Furthermore, QIN is a computationally efficient method compared with conventional interpolation methods that require the entire data space to be evaluated during interpolation, even if only a subset of the data space requires interpolation.

스마트 철도 네트워크를 위한 통신 구조 (Communication Structure for Smart Railway Network)

  • 김영동
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 춘계학술대회
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    • pp.197-199
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    • 2021
  • 고속화 되고 있는 철도 시스템은 각 구성 요소의 자동화를 넘어 이를 통합한 스마트 철도 네트워크로 진화되고 있다. 이와 같은 스마트 철도 네트워크를 구축하기 위해서는 LTE-R이나 5G-R과 같은 모바일 통신 기술 뿐만 아니라 AI, 빅데이터, 딥러닝과 같은 융복합 정보기술의 활용이 필수적이다. 본 연구에서는 이와 같이 스마트 철도 네트워크를 위한 철도 통신의 구조를 제안하고자 한다. 본 연구에서 제안하는 스마트 철도 네트워크 통신 구조는 고속철도의 안전 운행, 철도 관리 및 고객 서비스를 포괄하는 구조로 구성되며 필요에 따라 이를 혼합한 기능을 가질 수도 있다. 본 연구의 결과는 스마트 철도 네트워크의 구축과 운영 및 유지 관리, 철도통신 시스템 표준의 개발 등에 도움을 줄 수 있을 것으로 생각한다.

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Adversarial Attacks and Defense Strategy in Deep Learning

  • Sarala D.V;Thippeswamy Gangappa
    • International Journal of Computer Science & Network Security
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    • 제24권1호
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    • pp.127-132
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    • 2024
  • With the rapid evolution of the Internet, the application of artificial intelligence fields is more and more extensive, and the era of AI has come. At the same time, adversarial attacks in the AI field are also frequent. Therefore, the research into adversarial attack security is extremely urgent. An increasing number of researchers are working in this field. We provide a comprehensive review of the theories and methods that enable researchers to enter the field of adversarial attack. This article is according to the "Why? → What? → How?" research line for elaboration. Firstly, we explain the significance of adversarial attack. Then, we introduce the concepts, types, and hazards of adversarial attack. Finally, we review the typical attack algorithms and defense techniques in each application area. Facing the increasingly complex neural network model, this paper focuses on the fields of image, text, and malicious code and focuses on the adversarial attack classifications and methods of these three data types, so that researchers can quickly find their own type of study. At the end of this review, we also raised some discussions and open issues and compared them with other similar reviews.

Pile bearing capacity prediction in cold regions using a combination of ANN with metaheuristic algorithms

  • Zhou Jingting;Hossein Moayedi;Marieh Fatahizadeh;Narges Varamini
    • Steel and Composite Structures
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    • 제51권4호
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    • pp.417-440
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    • 2024
  • Artificial neural networks (ANN) have been the focus of several studies when it comes to evaluating the pile's bearing capacity. Nonetheless, the principal drawbacks of employing this method are the sluggish rate of convergence and the constraints of ANN in locating global minima. The current work aimed to build four ANN-based prediction models enhanced with methods from the black hole algorithm (BHA), league championship algorithm (LCA), shuffled complex evolution (SCE), and symbiotic organisms search (SOS) to estimate the carrying capacity of piles in cold climates. To provide the crucial dataset required to build the model, fifty-eight concrete pile experiments were conducted. The pile geometrical properties, internal friction angle 𝛗 shaft, internal friction angle 𝛗 tip, pile length, pile area, and vertical effective stress were established as the network inputs, and the BHA, LCA, SCE, and SOS-based ANN models were set up to provide the pile bearing capacity as the output. Following a sensitivity analysis to determine the optimal BHA, LCA, SCE, and SOS parameters and a train and test procedure to determine the optimal network architecture or the number of hidden nodes, the best prediction approach was selected. The outcomes show a good agreement between the measured bearing capabilities and the pile bearing capacities forecasted by SCE-MLP. The testing dataset's respective mean square error and coefficient of determination, which are 0.91846 and 391.1539, indicate that using the SCE-MLP approach as a practical, efficient, and highly reliable technique to forecast the pile's bearing capacity is advantageous.

2차원 지질시간 규모 수치지형발달모형의 개발 (Development of a 2 Dimensional Numerical Landscape Evolution Model on a Geological Time Scale)

  • 변종민;김종욱
    • 대한지리학회지
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    • 제46권6호
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    • pp.673-692
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    • 2011
  • 컴퓨터 기술의 발전으로 인해 근래 들어 수치지형발달모형을 개발하고 이를 이용하여 다양한 관점에서 지형발달과정의 역동성을 파악하기 위한 시도들이 활발하게 행해졌다. 하지만 국내에서는 수치지형발달모형을 활용하거나 개발하는 시도가 거의 없었다. 이에 본 연구에서는 2차원상에서 지질시간 규모의 지형발달을 모의하는 수치지형발달모형을 개발하고 이의 유용성을 확인해 보았다. 개발된 모형은 지표 구성물질을 기반암과 이동 가능한 토양으로 구분하고 토양층의 두께를 모의하기 위해 기반암 풍화를 포함한다. 이를 통해 사면에서는 운반제어환경뿐만이 아니라 풍화제어환경도 모의 가능하다. 또한 토양포행과 같은 사면에서의 점진적인 물질이동과는 별개로 활동(landslide) 역시 주요한 지형형성작용으로 포함한다. 그리고 하천 운반력이 하상물질의 양보다 큰 곳에서는 기반암 하상 침식이 발생하여 분리제어환경도 모의한다. 한편 무한 유향 알고리듬을 이용하여 흐름을 분배하기 때문에 최대하부 경사 유향 알고리듬을 이용할 때 나타나는 흐름 분배상의 문제점을 줄일 수 있다. 개발된 모형을 이용한 모의실험 결과, 본 모형은 지질시간 규모의 지형발달과정을 비교적 합리적으로 모의하였다.