讲座名称：No Training Hurdles: Fast Training-Agnostic Attacks to Infer Your Typing
讲座地点：腾讯会议直播（会议ID：174 533 274）
刘尧，南佛罗里达大学计算机科学与工程系的副教授，研究重点是设计和实施防御方法，以保护新兴的移动和网络技术不受对手的破坏，曾在网络和安全会议的组织和技术计划委员会中任职，包括NDSS，CCS，INFOCOM，S＆P和CNS。 她还是学术期刊的编辑委员会成员，包括《Jornal of Computer Security》和《 IEEETransactions on Information Forensics and Security》。 于2019年获得ACM SIGSAC颁发的ACM CCS Test-of-Time奖，于2016年获得NSF CAREER奖。
Traditional methods to eavesdrop keystrokes leverage some malware installed in a target computer to record the keystrokes for an adversary. Existing research work has identified a new class of attacks that can eavesdrop the keystrokes in a non-invasive way without infecting the target computer to install a malware. The common idea is that pressing a key of a keyboard can cause a unique and subtle environmental change, which can be captured and analyzed by the eavesdropper to learn the keystrokes. For these attacks, however, a training phase must be accomplished to establish the relationship between an observed environmental change and the action of pressing a specific key. This significantly limits the impact and practicality of these attacks. Recently, we discover that it is possible to design keystroke eavesdropping attacks without requiring the training phase. To eavesdrop keystrokes, an attacker can establish a mapping between typing each letter and its respective environmental change by exploiting the correlation among observed changes and known structures of dictionary words. This talk will introduce this new attack and the experiment results.