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Search: "[ author: 문종섭 ]" (41)
데이터 예측 클래스 기반 적대적 공격 탐지 및 분류 모델
고은나래,
문종섭,
Vol. 31, No. 6, pp. 1227-1236,
12월.
2021
10.13089/JKIISC.2021.31.6.1227
주제어: Adversarial attack, Evasion Attack, Deep Learning, Adversarial Example Detection
10.13089/JKIISC.2021.31.6.1227
주제어: Adversarial attack, Evasion Attack, Deep Learning, Adversarial Example Detection
무선 센서 네트워크에서 클러스터링 기반 Sleep Deprivation Attack 탐지 모델
김숙영,
문종섭,
Vol. 31, No. 1, pp. 83-97,
2월.
2021
10.13089/JKIISC.2021.31.1.83
주제어: Wireless Sensor Network, Sleep deprivation attack, S-MAC, energy efficiency., Wireless Sensor Network, Sleep deprivation attack, S-MAC, energy efficiency.
10.13089/JKIISC.2021.31.1.83
주제어: Wireless Sensor Network, Sleep deprivation attack, S-MAC, energy efficiency., Wireless Sensor Network, Sleep deprivation attack, S-MAC, energy efficiency.
Bidirectional Convolutional LSTM을 이용한 Deepfake 탐지 방법
이대현,
문종섭,
Vol. 30, No. 6, pp. 1053-1065,
12월.
2020
10.13089/JKIISC.2020.30.6.1053
주제어: Deepfake, LSTM, Attention module, Artificial intelligence, Time distribution., Deepfake, LSTM, Attention module, Artificial intelligence, Time distribution.
10.13089/JKIISC.2020.30.6.1053
주제어: Deepfake, LSTM, Attention module, Artificial intelligence, Time distribution., Deepfake, LSTM, Attention module, Artificial intelligence, Time distribution.
STFT와 RNN을 활용한 화자 인증 모델
김민서,
문종섭,
Vol. 29, No. 6, pp. 1393-1401,
12월.
2019
10.13089/JKIISC.2019.29.6.1393
주제어: Speaker verification, STFT, Deep Learning, Recurrent Neural Network(RNN), Speaker verification, STFT, Deep Learning, Recurrent Neural Network(RNN)
10.13089/JKIISC.2019.29.6.1393
주제어: Speaker verification, STFT, Deep Learning, Recurrent Neural Network(RNN), Speaker verification, STFT, Deep Learning, Recurrent Neural Network(RNN)
감쇠 요소가 적용된 데이터 어그멘테이션을 이용한 대체 모델 학습과 적대적 데이터 생성 방법
민정기,
문종섭,
Vol. 29, No. 6, pp. 1383-1392,
12월.
2019
10.13089/JKIISC.2019.29.6.1383
주제어: Deep Learning, Adversarial Data Generation, data augmentation, Deep Learning, Adversarial Data Generation, data augmentation
10.13089/JKIISC.2019.29.6.1383
주제어: Deep Learning, Adversarial Data Generation, data augmentation, Deep Learning, Adversarial Data Generation, data augmentation
Variational Autoencoder를 활용한 필드 기반 그레이 박스 퍼징 방법
이수림,
문종섭,
Vol. 28, No. 6, pp. 1463-1474,
11월.
2018
10.13089/JKIISC.2018.28.6.1463
주제어: Software Testing, Fuzzing, Vulnerability, Deep Learning, VAE(Variational Autoencoder), Software Testing, Fuzzing, Vulnerability, Deep Learning, VAE(Variational Autoencoder)
10.13089/JKIISC.2018.28.6.1463
주제어: Software Testing, Fuzzing, Vulnerability, Deep Learning, VAE(Variational Autoencoder), Software Testing, Fuzzing, Vulnerability, Deep Learning, VAE(Variational Autoencoder)
명령 실행 모니터링과 딥 러닝을 이용한 파워셸 기반 악성코드 탐지 방법
이승현,
문종섭,
Vol. 28, No. 5, pp. 1197-1207,
9월.
2018
10.13089/JKIISC.2018.28.5.1197
주제어: PowerShell, Malware, execution monitoring, Deep Learning, PowerShell, Malware, execution monitoring, Deep Learning
10.13089/JKIISC.2018.28.5.1197
주제어: PowerShell, Malware, execution monitoring, Deep Learning, PowerShell, Malware, execution monitoring, Deep Learning
