고려대학교 행정학과

2. 소속: Department of Computer Science, George Mason University, USA

3. 강의주제: Cybersecurity Using Adversarial Learning and Conformal Prediction

4. 일시 : 2015년 8월 24일 (월요일)  오전 11시~12시

5. 장소 : 미래융합기술관 601호 강당

Wechsler교수님은 Biometrics (생체인식)쪽 연구를 하셨던 분인데 이번에 WISA에서 초청강연차 한국에 오셨는데 이후 고려대학교에 하루정도 오셔서 강연을 하실 예정입니다. 특히, Wechsler교수님께서 최근 2015년에 쓴 논문내용을 직접 강연하실 예정입니다. 많은 참여 바랍니다.

관련내용은 http://www.scirp.org/journal/PaperInformation.aspx 에서 직접 찾을수 있으며, 초록은 아래와 같습니다.

초록 
This paper advances new directions for cyber security using adversarial learning and conformal prediction in order to enhance network and computing services defenses against adaptive, malicious, persistent, and tactical offensive threats. Conformal prediction is the principled and unified adaptive and learning framework used to design, develop, and deploy a multi-faceted self-managing defensive shield to detect, disrupt, and deny intrusive attacks, hostile and malicious behavior, and subterfuge. Conformal prediction leverages apparent relationships between immunity and intrusion detection using non-conformity measures characteristic of affinity, a typicality, and surprise, to recognize patterns and messages as friend or foe and to respond to them accordingly. The solutions proffered throughout are built around active learning, meta-reasoning, randomness, distributed semantics and stratification, and most important and above all around adaptive Oracles. The motivation for using conformal prediction and its immediate off-spring, those of semi-supervised learning and transduction, comes from them first and foremost supporting discriminative and non-parametric methods characteristic of principled demarcation using cohorts and sensitivity analysis to hedge on the prediction outcomes including negative selection, on one side, and providing credibility and confidence indices that assist meta-reasoning and information fusion.