거리기반 키스트로크 다이나믹스 스마트폰 인증과 임계값 공식 모델
Distance-Based Keystroke Dynamics Smartphone Authentication and Threshold Formula Model
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초록
비밀번호 입력 또는 잠금 패턴을 이용한 사용자 인증은 스마트폰의 사용자 인증 방식으로 널리 사용되고 있다. 하지만엿보기 공격 등에 취약하고 복잡도가 낮아 보안성이 낮다. 이러한 문제점을 보완하기 위해 키스트로크 다이나믹스를 인증에 적용하여 복합 인증을 하는 방식이 등장하였고 이에 대한 연구가 진행되어 왔다. 하지만, 많은 연구들이 분류기 학습에 있어서 비정상 사용자의 데이터를 함께 사용하고 있다. 키스트로크 다이나믹스를 실제 적용 시에는 정상 사용자의데이터만을 학습에 사용할 수 있는 것이 현실적이고, 타인의 데이터를 비정상 사용자 학습 데이터로 사용하는 것은 인증자료 유출 및 프라이버시 침해 등의 문제가 발생할 수 있다. 이에 대한 대응으로, 본 논문에서는 거리기반 분류기 사용에있어서, 분류 시 필요한 임계값의 최적 비율을 실험을 통해 구하고, 이를 밝힘으로써 실제 적용에서 정상 사용자 자료만을 이용하여 학습하고, 이 결과에 최적 비율을 적용하여 사용할 수 있도록 공헌하고자 한다.
Abstract
User authentication using PIN input or lock pattern is widely used as a user authentication method of smartphones. However, it is vulnerable to shoulder surfing attacks and because of low complexity of PIN and lock pattern, it has lowsecurity. To complement these problems, keystroke dynamics have been used as an authentication method for complexauthentication and researches on this have been in progress. However, many studies have used imposter data in classifiertraining and validation. When keystroke dynamics authentications are actually applied in reality, it is realistic to use onlylegitimate user data for training, and using other people's data as imposter training data may result in problems such asleakage of authentication data and invasion of privacy. In response, in this paper, we experiment and obtain the optimalratio of the thresholds for distance based classification. By suggesting the optimal ratio, we try to contribute to the realapplications of keystroke authentications.
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