ScholarWorks@Soongsil University: Choi, Daeseon

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Choi, Daeseon (최대선)

College of Information Technology (School of Software)

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machine learning:7||adversarial example:6||Machine learning:5||Privacy:4||Authentication:4||Machine Learning:4||Deep neural network:3||Federated learning:3||Deep neural network (DNN):3||deep neural network:3||security:3||adversarial attack:3||Adversarial Example:3||Security:3||Big Data:2||Logon Type:2||Adversarial defense:2||poisoning attack:2||privacy:2||URL protocol spoofing attack:2||Deidentification:2||Deep neural networks:2||Adversarial example:2||Adversarial examples:2||SNS:2||Feature extraction:2||evasion attack:2||implicit authentication:2||HBOS:2||authentication:2||Personal Information:2||autoencoder:2||Smartphone Security:2||Evasion Attack:2||backdoor attack:2||Key management:2||Evasion attack:2||기계학습:2||AI security:2||LANL2015:2||Pricacy:2||Adversarial attack:2||Downscaling:1||EEG:1||Ensemble method:1||Exploratory Attack:1||Exponentiation:1||FIDO standard:1||FROST (Flexible RoundOptimized Schnorr Threshold Signatures):1||Face privacy:1||Face recognition:1||Face verification:1||Facebook:1||Feature selection:1||Federated Learning:1||FinTech:1||Financial data:1||Fraud Detection:1||Game fraud:1||Gender:1||Generative Adversarial Network:1||Generative Adversarial Networks:1||Generative Model:1||Genetic algorithm:1||Identification:1||Identity Proofing:1||Image Classification:1||Image color analysis:1||Inference Attack:1||Inference attack:1||Information Security:1||KAnonymity:1||Kanonmity:1||Kanonymity:1||Korean residence registration number:1||Ldiversity:1||Leakage attack:1||Location Information:1||Magnetic secure transmission:1||Marital/relationship status:1||Membership Inference Attack:1||Mobile Signature:1||Mobile biometric:1||MultiSensor Fusion:1||NoPlugin:1||NonFacetoFace:1||One Class:1||P2P lending:1||P2P 대출:1||Payment:1||Personal Information Security:1||Personal information:1||Perturbation methods:1||Plugin:1||Poisoning attack:1||Privacy analysis:1||Private attribute:1||Public Key Certificate:1||Purification network:1||QR code:1||QR코드:1||Reidentification:1||Reconstruction Attack:1||Reconstruction attack:1||Resident Registration Number:1||SMS authentication:1||SNS security:1||Samsung pay:1||Signature:1||Small exponent test:1||Smart Pad:1||Smart Phone:1||Smart TV:1||Social Network Service:1||Speech deidentification:1||Speech deidentification model:1||Standards:1||Substitute model:1||Symbolic Representation:1||Tcloseness:1||TexttoImage Model:1||Textual Inversion:1||Tomek Links method:1||Tomek Links 방법:1||Training:1||Trust management:1||URL 프로토콜 위장 공격:1||User Authentication:1||Vehicle Privacy:1||Voice modulation:1||WACI (Wallet And Credential Interaction):1||Web service attacks:1||access pattern:1||adversarial defense:1||adversarial training:1||anonymization:1||artificial intelligence:1||artificial intelligence security:1||artificial neural networks:1||authorization:1||autoencoder neural network:1||avoided classes:1||balancing GAN:1||behavior analysis:1||biometric:1||clustering algorithm:1||contextaware:1||continuous authentication:1||convolution neural network:1||credit data:1||credit information:1||data estimation:1||data leakage prevention:1||deep convolutional network:1||deep neural network (DNN):1||default predict:1||denial of service (DoS):1||dynamic signature:1||dynamic time warping:1||electronic commerce:1||ensemble adversarial example:1||environment analysis:1||face classification:1||filtering:1||generative adversarial network:1||image synthesis:1||imbalanced data:1||imperceptibility:1||interoperability technology of digital identification:1||intrusiontolerant system:1||investment information:1||learning (artificial intelligence):1||local smoothness:1||location of interest:1||mobile payment:1||mobile security:1||multiagent reinforcement learning:1||multimodal authentication:1||multiparty distributed signature:1||network intrusion detection system:1||neural network:1||neural networks:1||numerical dataset:1||optimal cluster expansion:1||peertopeer network:1||personal data security:1||personal information:1||point of sale:1||public information:1||queuing theory:1||random selection:1||reidentification:1||recurrent neural network:1||recursive neural network (RNN):1||reinforcement learinng:1||restricted area:1||searchable symmetric encryption:1||sharing:1||singer authentication:1||skilled forgery:1||social network:1||speech recognition:1||statistic analysis:1||steganalysisbased detection:1||synthesis data:1||tabular dataset:1||time series analysis:1||transferability:1||trust evaluation:1||universal digital wallet:1||untargeted adversarial example:1||virtual machine (VM):1||wireless networks:1||개방공유:1||공공정보:1||공인인증서:1||보안:1||불균형 데이터:1||비대면:1||사용자 인증:1||소셜 네트워크:1||수치 데이터 세트:1||순환신경망:1||스마트TV:1||스마트패드:1||스마트폰:1||스마트폰 보안:1||시계열 분석:1||신용정보:1||음성 변조:1||음성 비식별화:1||음성 비식별화 모델:1||이상행위탐지:1||익명화:1||인증:1||재식별:1||전자서명:1||지불:1||채무불이행 예측:1||키 관리:1||통계 분석:1||투자정보:1||특성 추출:1||표 데이터 세트:1||플러그인:1||핀테크. 빅데이터:1||AE:1||필터링:1||Account Takeover:1||Adversarial Prompt:1||Adversarial training:1||Age:1||Anomaly Detection:1||Anonymization:1||AutoEncoder:1||Autonomous Driving:1||BCI:1||Balancing GAN:1||Batch verification:1||Bio Signal:1||Biometric Recognition:1||Biometrics:1||Blackbox attack:1||Browser Fingerprinting:1||CAPTCHA:1||CameraLiDAR Calibration model:1||Chargeback fraud detection:1||Classification score:1||Covert Channel:1||Customized filtering:1||Data Privacy:1||Data Reconstruction:1||Data correction:1||Data crawling:1||Data inference:1||Database security:1||Deidentification Algorithms:1||Decisionbased attack:1||Deep Neural Network:1||Deep learning:1||Denoising network:1||Detection method:1||Detectors:1||Device Fingerprinting:1||Differential privacy:1||Differentialprivacy:1||Digital Signature:1||Digital signature:1||Distortion:1||

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