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Search: "[ keyword: Machine Learning ]" (52)
AI를 통한 BEC (Business Email Compromise) 공격의 효과적인 대응방안 연구
이도경,
장건수,
이경호,
Vol. 30, No. 5, pp. 835-846,
10월.
2020
10.13089/JKIISC.2020.30.5.835
주제어: Business email compromise, BEC, SCAM, Social Engineering, email attack, Machine Learning, Business email compromise, BEC, SCAM, Social Engineering, email attack, Machine Learning
10.13089/JKIISC.2020.30.5.835
주제어: Business email compromise, BEC, SCAM, Social Engineering, email attack, Machine Learning, Business email compromise, BEC, SCAM, Social Engineering, email attack, Machine Learning
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
10.13089/JKIISC.2019.29.6.1327
주제어: Linux Malware, Machine Learning, Static Analysis, Linux Malware, Machine Learning, Static Analysis
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
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
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
10.13089/JKIISC.2019.29.4.775
주제어: Malware, Machine Learning, Feature statistics, Packer, Similarity hashing
신경망을 이용한 소프트웨어 취약 여부 예측 시스템
최민준,
구동영,
윤수범,
Vol. 29, No. 3, pp. 557-564,
6월.
2019
10.13089/JKIISC.2019.29.3.557
주제어: Artificial intelligence, Neural Network, Machine Learning, Fuzzing, software vulnerability, Artificial intelligence, Neural Network, Machine Learning, Fuzzing, software vulnerability
10.13089/JKIISC.2019.29.3.557
주제어: Artificial intelligence, Neural Network, Machine Learning, Fuzzing, software vulnerability, Artificial intelligence, Neural Network, Machine Learning, Fuzzing, software vulnerability
악성코드 분석의 Ground-Truth 향상을 위한 Unified Labeling과 Fine-Grained 검증
오상진,
박래현,
권태경,
Vol. 29, No. 3, pp. 549-555,
6월.
2019
10.13089/JKIISC.2019.29.3.549
주제어: Malware, Labeling, Machine Learning, clustering, Malware, Labeling, Machine Learning, clustering
10.13089/JKIISC.2019.29.3.549
주제어: Malware, Labeling, Machine Learning, clustering, Malware, Labeling, Machine Learning, clustering
제조공정 단말PC 작업자 접속 로그를 통한 이상 징후 탐지 모델 연구
안종성,
이경호,
Vol. 29, No. 2, pp. 321-330,
4월.
2019
10.13089/JKIISC.2019.29.2.321
주제어: Machine Learning, Anomaly Detection, Feature selection, Machine Learning, Anomaly Detection, Feature selection
10.13089/JKIISC.2019.29.2.321
주제어: Machine Learning, Anomaly Detection, Feature selection, Machine Learning, Anomaly Detection, Feature selection
기계학습 기반 비트코인 채굴 난이도 예측 연구
이준원,
권태경,
Vol. 29, No. 1, pp. 225-234,
2월.
2019
10.13089/JKIISC.2019.29.1.225
주제어: Bitcoin, Mining difficulty, Time-series analysis, Predictive model, Machine Learning, Bitcoin, Mining difficulty, Time-series analysis, Predictive model, Machine Learning
10.13089/JKIISC.2019.29.1.225
주제어: Bitcoin, Mining difficulty, Time-series analysis, Predictive model, Machine Learning, Bitcoin, Mining difficulty, Time-series analysis, Predictive model, Machine Learning
