When Eye-Tracking Meets Cognitive Modeling: Applications to Cyber Security Systems

Human cognitive modeling techniques and related software tools have been widely used by researchers and practitioners to evaluate the effectiveness of user interface (UI) designs and related human performance. However, they are rarely used in the cyber security field despite the fact that human factors have been recognized as a key element for cyber security systems. For a cyber security system involving a relatively complicated UI, it could be difficult to build a cognitive model that accurately captures the different cognitive tasks involved in all user interactions. Using a moderately complicated user authentication system as an example system and CogTool as a typical cognitive modeling tool, this paper aims to provide insights into the use of eye-tracking data for facilitating human cognitive modeling of cognitive tasks more effectively and accurately. We used visual scan paths extracted from an eye-tracking user study to facilitate the design of cognitive modeling tasks. This allowed us to reproduce some insecure human behavioral patterns observed in some previous lab-based user studies on the same system, and more importantly, we also found some unexpected new results about human behavior. The comparison between human cognitive models with and without eye-tracking data suggests that eye-tracking data can provide useful information to facilitate the process of human cognitive modeling as well as to achieve a better understanding of security-related human behaviors. In addition, our results demonstrated that cyber security research can benefit from a combination of eye-tracking and cognitive modeling to study human behavior related security problems

Transcriptional control in the prereplicative phase of T4 development

Control of transcription is crucial for correct gene expression and orderly development. For many years, bacteriophage T4 has provided a simple model system to investigate mechanisms that regulate this process. Development of T4 requires the transcription of early, middle and late RNAs. Because T4 does not encode its own RNA polymerase, it must redirect the polymerase of its host, E. coli, to the correct class of genes at the correct time. T4 accomplishes this through the action of phage-encoded factors. Here I review recent studies investigating the transcription of T4 prereplicative genes, which are expressed as early and middle transcripts. Early RNAs are generated immediately after infection from T4 promoters that contain excellent recognition sequences for host polymerase. Consequently, the early promoters compete extremely well with host promoters for the available polymerase. T4 early promoter activity is further enhanced by the action of the T4 Alt protein, a component of the phage head that is injected into E. coli along with the phage DNA. Alt modifies Arg265 on one of the two α subunits of RNA polymerase. Although work with host promoters predicts that this modification should decrease promoter activity, transcription from some T4 early promoters increases when RNA polymerase is modified by Alt. Transcription of T4 middle genes begins about 1 minute after infection and proceeds by two pathways: 1) extension of early transcripts into downstream middle genes and 2) activation of T4 middle promoters through a process called sigma appropriation. In this activation, the T4 co-activator AsiA binds to Region 4 of σ70, the specificity subunit of RNA polymerase. This binding dramatically remodels this portion of σ70, which then allows the T4 activator MotA to also interact with σ70. In addition, AsiA restructuring of σ70 prevents Region 4 from forming its normal contacts with the -35 region of promoter DNA, which in turn allows MotA to interact with its DNA binding site, a MotA box, centered at the -30 region of middle promoter DNA. T4 sigma appropriation reveals how a specific domain within RNA polymerase can be remolded and then exploited to alter promoter specificity