The Universal Serial Bus (USB) is becoming a prevalent attack vector. Rubber Ducky and BadUSB are two recent classes of a whole spectrum of attacks carried out using fully-automated keypress injections through innocent-looking USB devices. So far, defense mechanisms are insufficient and rely on user participation in the trust decision. We propose USBlock, a novel approach to detect suspicious USB devices by analyzing the temporal characteristics of the USB packet traffic they generate, similarly to intrusion detection approaches in networked systems. Our approach is unique in that it does not to involve at all the user in the trust decision. We describe a proof-of-concept implementation for Linux and we assess the effectiveness and efficiency of our approach to cope with temporal variations in typing habits and dynamics of legitimate users.
At the time of writing, one of the most pressing problems for forensic investigators is the huge amount of data to analyze per case. Not only the number of devices increases due to the advancing computerization of everydays life, but also the storage capacity of each and every device raises into multiterabyte storage requirements per case for forensic working images. In this paper we improve the standardized forensic process by proposing to use file deduplication across devices as well as file whitelisting rigorously in investigations, to reduce the amount of data that needs to be stored for analysis as early as during data acquisition. These improvements happen in an automatic fashion and completely transparent to the forensic investigator. They furthermore be added without negative effects to the chain of custody or artefact validity in court, and are evaluated in a realistic use case.
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