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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
주제어: Deep Learning, Adversarial Data Generation, data augmentation, Deep Learning, Adversarial Data Generation, data augmentation
정적 분석과 앙상블 기반의 리눅스 악성코드 분류 연구
황준호,
이태진,
Vol. 29, No. 6, pp. 1327-1337,
12월.
2019
10.13089/JKIISC.2019.29.6.1327
주제어: Linux Malware, Machine Learning, Static Analysis, Linux Malware, Machine Learning, Static Analysis
주제어: Linux Malware, Machine Learning, Static Analysis, Linux Malware, Machine Learning, Static Analysis
원전디지털자산 사이버보안 규제 요건 개발을 위한 보안조치 적용 방안에 대한 분석
김인경,
변예은,
권국희,
Vol. 29, No. 5, pp. 1077-1088,
10월.
2019
10.13089/JKIISC.2019.29.5.1077
주제어: Nuclear digital assets, Cyber Security, Regulation, Nuclear digital assets, Cyber Security, Regulation
주제어: Nuclear digital assets, Cyber Security, Regulation, Nuclear digital assets, Cyber Security, Regulation
Multi-Layer Perceptron 기법을 이용한 전력 분석 공격 구현 및 분석
권홍필,
배대현,
하재철,
Vol. 29, No. 5, pp. 997-1006,
10월.
2019
10.13089/JKIISC.2019.29.5.997
주제어: Side-Channel Analysis, Power Analysis Attack, Deep Learning MLP, Machine Learning SVM, Side-Channel Analysis, Power Analysis Attack, Deep Learning MLP, Machine Learning SVM
주제어: Side-Channel Analysis, Power Analysis Attack, Deep Learning MLP, Machine Learning SVM, Side-Channel Analysis, Power Analysis Attack, Deep Learning MLP, Machine Learning SVM
네트워크 데이터 정형화 기법을 통한 데이터 특성 기반 기계학습 모델 성능평가
이우호,
노봉남,
정기문,
Vol. 29, No. 4, pp. 785-794,
8월.
2019
10.13089/JKIISC.2019.29.4.785
주제어: IDS, Deep Learning, Data normalize
주제어: IDS, Deep Learning, Data normalize
정적 분석 기반 기계학습 기법을 활용한 악성코드 식별 시스템 연구
김수정,
하지희,
오수현,
이태진,
Vol. 29, No. 4, pp. 775-784,
8월.
2019
10.13089/JKIISC.2019.29.4.775
주제어: Malware, Machine Learning, Feature statistics, Packer, Similarity hashing
주제어: Malware, Machine Learning, Feature statistics, Packer, Similarity hashing
Variational Autoencoder를 활용한 필드 기반 그레이 박스 퍼징 방법
이수림,
문종섭,
Vol. 28, No. 6, pp. 1463-1474,
12월.
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)
주제어: Software Testing, Fuzzing, Vulnerability, Deep Learning, VAE(Variational Autoencoder), Software Testing, Fuzzing, Vulnerability, Deep Learning, VAE(Variational Autoencoder)
분석적 방법을 적용한 원전디지털자산 취약점 평가 연구
김인경,
권국희,
Vol. 28, No. 6, pp. 1539-1552,
12월.
2018
10.13089/JKIISC.2018.28.6.1539
주제어: Nuclear digital assets, Control system cyber security, Vulnerability Assessment, Nuclear digital assets, Control system cyber security, Vulnerability Assessment
주제어: Nuclear digital assets, Control system cyber security, Vulnerability Assessment, Nuclear digital assets, Control system cyber security, Vulnerability Assessment
LWE와 LWR을 이용한 효율적인 다중 비트 암호화 기법
장초롱,
서민혜,
박종환,
Vol. 28, No. 6, pp. 1329-1342,
12월.
2018
10.13089/JKIISC.2018.28.6.1329
주제어: Post-Quantum Cryptography, Lattice-based cryptography, Learning with errors, Learning with rounding, Post-Quantum Cryptography, Lattice-based cryptography, Learning with errors, Learning with rounding
주제어: Post-Quantum Cryptography, Lattice-based cryptography, Learning with errors, Learning with rounding, Post-Quantum Cryptography, Lattice-based cryptography, Learning with errors, Learning with rounding
Filter Method와 Classification 알고리즘을 이용한 전자상거래 블랙컨슈머 탐지에 대한 연구
이태규,
이경호,
Vol. 28, No. 6, pp. 1499-1508,
12월.
2018
10.13089/JKIISC.2018.28.6.1499
주제어: Machine Learning, Supervised Learning, Fraud Detection, User Classification, Feature selection, Machine Learning, Supervised Learning, Fraud Detection, User Classification, Feature selection
주제어: Machine Learning, Supervised Learning, Fraud Detection, User Classification, Feature selection, Machine Learning, Supervised Learning, Fraud Detection, User Classification, Feature selection