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Search: "[ keyword: Deep Learning ]" (41)
선형 판별 분석 및 k-means 알고리즘을 이용한 적대적 공격 유형 분류 방안
최석환,
김형건,
최윤호,
Vol. 31, No. 6, pp. 1215-1225,
12월.
2021
10.13089/JKIISC.2021.31.6.1215
주제어: Deep Learning, Adversarial example, Adversarial attack, clustering
![](https://d2kjln74dkk4oj.cloudfront.net/img/doi_icon.png)
주제어: Deep Learning, Adversarial example, Adversarial attack, clustering
연속 웨이블릿 변환을 사용한 비프로파일링 기반 전력 분석 공격
배대현,
이재욱,
하재철,
Vol. 31, No. 6, pp. 1127-1136,
12월.
2021
10.13089/JKIISC.2021.31.6.1127
주제어: Implementation Attack, Hardware Security, Artificial intelligence, Deep Learning, wavelet transform
![](https://d2kjln74dkk4oj.cloudfront.net/img/doi_icon.png)
주제어: Implementation Attack, Hardware Security, Artificial intelligence, Deep Learning, wavelet transform
입력 변이에 따른 딥러닝 모델 취약점 연구 및 검증
김재욱,
박래현,
권태경,
Vol. 31, No. 1, pp. 51-59,
2월.
2021
10.13089/JKIISC.2021.31.1.51
주제어: Deep Learning, Mutation, Adversarial machine learning, Deep Learning, Mutation, Adversarial machine learning
![](https://d2kjln74dkk4oj.cloudfront.net/img/doi_icon.png)
주제어: Deep Learning, Mutation, Adversarial machine learning, Deep Learning, Mutation, Adversarial machine learning
효과적인 딥러닝 기반 비프로파일링 부채널 분석 모델 설계방안
한재승,
심보연,
임한섭,
김주환,
한동국,
Vol. 30, No. 6, pp. 1291-1300,
12월.
2020
10.13089/JKIISC.2020.30.6.1291
주제어: Side-Channel Analysis, Deep Learning, Multi Layer Perceptron, AES, Side-Channel Analysis, Deep Learning, Multi Layer Perceptron, AES
![](https://d2kjln74dkk4oj.cloudfront.net/img/doi_icon.png)
주제어: Side-Channel Analysis, Deep Learning, Multi Layer Perceptron, AES, Side-Channel Analysis, Deep Learning, Multi Layer Perceptron, AES
지터에 강건한 딥러닝 기반 프로파일링 부채널 분석 방안
김주환,
우지은,
박소연,
김수진,
한동국,
Vol. 30, No. 6, pp. 1271-1278,
12월.
2020
10.13089/JKIISC.2020.30.6.1271
주제어: Side-Channel Analysis, Deep Learning, Jitter, Global Average Pooling, AES, Side-Channel Analysis, Deep Learning, Jitter, Global Average Pooling, AES
![](https://d2kjln74dkk4oj.cloudfront.net/img/doi_icon.png)
주제어: Side-Channel Analysis, Deep Learning, Jitter, Global Average Pooling, AES, Side-Channel Analysis, Deep Learning, Jitter, Global Average Pooling, AES
기계학습을 이용한 소스코드 정적 분석 개선에 관한 연구
박양환,
최진영,
Vol. 30, No. 6, pp. 1131-1139,
12월.
2020
10.13089/JKIISC.2020.30.6.1131
주제어: Static Analysis, Secure Coding, Deep Learning, Convolutional Neural Networks(CNN), Static Analysis, Secure Coding, Deep Learning, Convolutional Neural Networks(CNN)
![](https://d2kjln74dkk4oj.cloudfront.net/img/doi_icon.png)
주제어: Static Analysis, Secure Coding, Deep Learning, Convolutional Neural Networks(CNN), Static Analysis, Secure Coding, Deep Learning, Convolutional Neural Networks(CNN)
멜트다운 취약점을 이용한 인공신경망 추출 공격
정호용,
류도현,
허준범,
Vol. 30, No. 6, pp. 1031-1041,
12월.
2020
10.13089/JKIISC.2020.30.6.1031
주제어: Meltdown, neural network stealing, Cloud computing, Deep Learning, Meltdown, neural network stealing, Cloud computing, Deep Learning
![](https://d2kjln74dkk4oj.cloudfront.net/img/doi_icon.png)
주제어: Meltdown, neural network stealing, Cloud computing, Deep Learning, Meltdown, neural network stealing, Cloud computing, Deep Learning
딥러닝을 활용한 전략물자 판정 지원도구 개발에 대한 연구
조재영,
윤지원,
Vol. 30, No. 6, pp. 967-973,
12월.
2020
10.13089/JKIISC.2020.30.6.967
주제어: Deep Learning, Classification, CNN, OCR, Dual-use Item, Deep Learning, Classification, CNN, OCR, Dual-use Item
![](https://d2kjln74dkk4oj.cloudfront.net/img/doi_icon.png)
주제어: Deep Learning, Classification, CNN, OCR, Dual-use Item, Deep Learning, Classification, CNN, OCR, Dual-use Item
CNN을 이용한 소비 전력 파형 기반 명령어 수준 역어셈블러 구현
배대현,
하재철,
Vol. 30, No. 4, pp. 527-536,
8월.
2020
10.13089/JKIISC.2020.30.4.527
주제어: Side-Channel Attack, power analysis, Deep Learning, Convolutional Neural Network(CNN), Disassembl, Side-Channel Attack, power analysis, Deep Learning, Convolutional Neural Network(CNN), Disassembl
![](https://d2kjln74dkk4oj.cloudfront.net/img/doi_icon.png)
주제어: Side-Channel Attack, power analysis, Deep Learning, Convolutional Neural Network(CNN), Disassembl, Side-Channel Attack, power analysis, Deep Learning, Convolutional Neural Network(CNN), Disassembl