연구동향 분석

네트워크 공격 탐지 성능향상을 위한 딥러닝을 이용한 트래픽 데이터 생성 연구

이우호 함재균 정현미 정기문 2019년

논문상세정보
인용/피인용
' 네트워크 공격 탐지 성능향상을 위한 딥러닝을 이용한 트래픽 데이터 생성 연구' 의 주제별 논문영향력
논문영향력 선정 방법
논문영향력 요약
주제
  • GAN
  • Deep learning
  • Intrusion detection
  • Network security
  • Network traffic data
  • 네트워크 보안
  • 네트워크 트래픽 데이터
  • 딥 러닝
  • 침입 탐지
동일주제 총논문수 논문피인용 총횟수 주제별 논문영향력의 평균
3,436 0

0.0%

' 네트워크 공격 탐지 성능향상을 위한 딥러닝을 이용한 트래픽 데이터 생성 연구' 의 참고문헌

  • kdd aRCHIVE. KDDcup99dataset
  • UNSW-NB15: a comprehensive data set for network intrusion detection systems (UNSW-NB15 network data set)
    N. Moustafa [2015]
  • Seqgan: Sequence generative adversarial nets with policy gradient
    L. Yu [2017]
  • SMOTE: synthetic minority over-sampling technique
  • Rectified linear units improve restricted boltzmann machines
    V. Nair [2010]
  • Network traffic classifier with convolutional and recurrent neural networks for internet of things
  • Malware traffic classification using convolutional neural network for representation learning
    W. WANG [2017]
  • MSMOTE: Improving classification performance when training data is imbalanced
    S. Hu [2009]
  • Improved adaptive Gaussian mixture model for background subtraction
    Z. Zivkovic [2004]
  • Efficient estimation of word representations in vector space
  • Deep learning for network flow analysis and malware classification
    R. K. Rahul [2017]
  • Comparison deep learning method to traditional methods using for network intrusion detection
    B. Dong [2016]
  • Character-level convolutional networks for text classification
    X. Zhang [2015]
  • Bayesian neural networks for internet traffic classification
    T. Auld [2007]
  • Anomalous payload-based network intrusion detection
    K. Wang [2004]
  • A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification
    N. Williams [2006]
  • A Study on NSL-KDD Dataset for Intrusion Detection System Based on Classification Algorithms
    L. Dhanabal [2015]