Matching Items (5)
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- All Subjects: Cognitive Psychology
- All Subjects: Time Delay
- Genre: Doctoral Dissertation
- Creators: Gray, Rob
Description
Cyber operations are a complex sociotechnical system where humans and computers are operating in an environments in constant flux, as new technology and procedures are applied. Once inside the network, establishing a foothold, or beachhead, malicious actors can collect sensitive information, scan targets, and execute an attack.Increasing defensive capabilities through cyber deception shows great promise by providing an opportunity to delay and disrupt an attacker once network perimeter security has already been breached. Traditional Human Factors research and methods are designed to mitigate human limitations (e.g., mental, physical) to improve performance. These methods can also be used combatively to upend performance. Oppositional Human Factors (OHF), seek to strategically capitalize on cognitive limitations by eliciting decision-making errors and poor usability. Deceptive tactics to elicit decision-making biases might infiltrate attacker processes with uncertainty and make the overall attack economics unfavorable and cause an adversary to make mistakes and waste resources.
Two online experimental platforms were developed to test the Sunk Cost Fallacy in an interactive, gamified, and abstracted version of cyber attacker activities. This work presents the results of the Cypher platform. Offering a novel approach to understand decision-making and the Sunk Cost Fallacy influenced by factors of uncertainty, project completion and difficulty on progress decisions. Results demonstrate these methods are effective in delaying attacker forward progress, while further research is needed to fully understand the context in which decision-making limitations do and do not occur. The second platform, Attack Surface, is described. Limitations and lessons learned are presented for future work.
ContributorsJohnson, Chelsea Kae (Author) / Gutzwiller, Robert S (Thesis advisor) / Cooke, Nancy (Committee member) / Shade, Temmie (Committee member) / Ferguson-Walter, Kimberly (Committee member) / Roscoe, Rod (Committee member) / Gray, Rob (Committee member) / Arizona State University (Publisher)
Created2022
Description
Maintaining upright balance and postural control is a task that most individuals perform everyday with ease and without much thought. Although it may be a relatively easy task to perform, research has shown that changes in cognitive (or “attentional”) processes are reflected in the movements of sway. The purpose of this dissertation is to understand the relationship between attention and posture when attention is directly or indirectly shifted away from posture. Using a dual-task paradigm, attention was shifted directly by instructing participants to prioritize the balance task (minimize sway in a unipedal stance) or prioritize the cognitive task (minimize errors in an auditory n-back task) and indirectly by changing the difficulty level of the cognitive task (0-back vs. 2-back task). Postural sway was assessed using sample entropy (SampEn), standard deviation, (SD) and sway path (SP) of trunk movements to measure the regularity, variability, and overall distance of sway travelled, respectively. Dual-task behavior was examined when participants were in a controlled (i.e., non-fatigued) state (Experiment 1), in a state of physical fatigue (Experiment 2), and in a state of mental fatigue (Experiment 3). Across all three experiments, indirectly shifting attention away from posture in the more difficult 2-back task induced less regularity (higher SampEn) and variability (smaller SD) in postural sway. Directly shifting attention away from posture, by prioritizing the cognitive task, induced less regularity (higher SampEn) and a longer path length (higher SP) in Experiment 1, however this effect was not significant for the fatigued participants in Experiments 2 and 3. Neither physical fatigue (Experiment 2) or mental fatigue (Experiment 3) negatively affected postural sway or cognitive performance. Overall, the findings from this dissertation contribute to the relationship between movement regularity and attention in posture, and that the postural behavior that emerges is sensitive to methods in which attention is manipulated (direct, indirect) and fatigue (physical, mental).
ContributorsGibbons, Cameron Todd (Author) / Amazeen, Polemnia G (Thesis advisor) / Amazeen, Eric L (Committee member) / Gray, Rob (Committee member) / Brewer, Gene A. (Committee member) / Arizona State University (Publisher)
Created2019
Description
This study investigated the ability to relate a test taker’s non-verbal cues during online assessments to probable cheating incidents. Specifically, this study focused on the role of time delay, head pose and affective state for detection of cheating incidences in a lab-based online testing session. The analysis of a test taker’s non-verbal cues indicated that time delay, the variation of a student’s head pose relative to the computer screen and confusion had significantly statistical relation to cheating behaviors. Additionally, time delay, head pose relative to the computer screen, confusion, and the interaction term of confusion and time delay were predictors in a support vector machine of cheating prediction with an average accuracy of 70.7%. The current algorithm could automatically flag suspicious student behavior for proctors in large scale online courses during remotely administered exams.
ContributorsChuang, Chia-Yuan (Author) / Femiani, John C. (Thesis advisor) / Craig, Scotty D. (Thesis advisor) / Bekki, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015
Description
Social categories such as race and gender are associated by people with certain characteristics (e.g. males are angry), which unconsciously affects how people evaluate and react to a person of specific social categories. This phenomenon, referred to as implicit bias, has been the interest of many social psychologists. However, the implicit bias research has been focusing on only one social category at a time, despite humans being entities of multiple social categories. The research also neglects the behavioral contexts in which implicit biases are triggered and rely on a broad definition for the locus of the bias regulation mechanism. These limitations raise questions on whether the current bias reduction strategies are effective. The current dissertation sought to address these limitations by introducing an ecologically valid and multidimensional method. In Chapters 1 and 2, the mouse-tracking task was integrated into the implicit association task to examine how implicit biases were moderated in different behavioral contexts. The results demonstrated that the manifestation of implicit biases depended on the behavioral context as well as the distinctive identity created by the combinations of different social categories. Chapter 3 laid groundwork for testing working memory as the processing capacity for the bias regulation mechanism. The result suggested that the hand-motion tracking indices of working memory load could be used to infer the capacity of an individual to suppress the influence of implicit bias. In Chapter 4, the mouse-tracking paradigm was integrated into the Stroop task with implicit associations serving as the Stroop targets. The implicit associations produced various effects including the conflict adaptation effect, like the Stroop targets, which suggested that implicit associations and Stroop stimuli are handled by overlapping cognitive mechanisms. Throughout these efforts, the current dissertation, first, demonstrated that a more ecologically valid and multidimensional approach is required to understand biased behaviors in detail. Furthermore, the current dissertation suggested the cognitive control mechanism as a finer definition for the locus of the bias regulation mechanism, which could be leveraged to offer solutions that are more adaptive and effective in the environment where collaboration and harmony are more important than ever.
ContributorsRheem, Hansol (Author) / Becker, D. Vaughn (Thesis advisor) / Craig, Scotty D. (Committee member) / Gutzwiller, Robert S. (Committee member) / Arizona State University (Publisher)
Created2019
Description
In order to perceive the heaviness of an object, one must wield it. This requires muscle activity and its resulting movements. Research has shown that muscle activity and movement combine for this perception in a manner inspired by Newton’s 2nd Law of Motion. Research in this area has relied on specific movement and muscle activity measures that often capture one moment of a lift. The current set of experiments set out to determine which measures best capture the underlying phenomena that lead to heaviness perception during a lift. In the first experiment, participants lifted stimuli with an elbow flexion lift while their muscle activity and movement were recorded. Participants reported their perceived heaviness of the stimuli as soon as they reached it, which resulted in an average decision angle of around 30-degrees. In the second and third experiments, participants the same stimuli with the same elbow flexion lift in four perturbation conditions – they experienced perturbations at 15-degrees of the lift, 30-degrees, 45-degrees, and with no perturbation. In the second experiment, participants experienced a physical perturbation and a cognitive perturbation in the third experiment. Across Experiments 2 and 3, the pattern of results suggested that the more time participants have in a lift, the more proportion correct, muscle activity, and movement measures appears like they do in the no perturbation condition. Additionally, a logistic least absolute shrinkage and selection operator (LASSO) regression was used to determine which measures best predicted perception. Results show that the integrated electromyogram of the biceps brachii that occurs after peak acceleration (iEMG BB after pACC) and Average Acceleration, which are both measures that capture more than one point of a lift, predicted heaviness perception. A new model of heaviness perception was then developed, using these new measures. Comparing this New Model to an Original Model from Waddell et al., 2016 resulted in better prediction from the New Model – suggesting that measure that capture more of a lift better predict heaviness perception, meaning that an entire ongoing action event is important for perception.
ContributorsWaddell, Morgan Leigh (Author) / Amazeen, Eric L (Thesis advisor) / Amazeen, Polemnia G (Committee member) / Glenberg, Arthur M (Committee member) / Gray, Rob (Committee member) / Arizona State University (Publisher)
Created2021