Man vs. machine: Investigating the effects of adversarial system use on end-user behavior in automated deception detection interviews

Deception is an inevitable component of human interaction. Researchers and practitioners are developing information systems to aid in the detection of deceptive communication. Information systems are typically adopted by end users to aid in completing a goal or objective (e.g., increasing the efficiency of a business process). However, end-user interactions with deception detection systems (adversarial systems) are unique because the goals of the system and the user are orthogonal. Prior work investigating systems-based deception detection has focused on the identification of reliable deception indicators. This research extends extant work by looking at how users of deception detection systems alter their behavior in response to the presence of guilty knowledge, relevant stimuli, and system knowledge. An analysis of data collected during two laboratory experiments reveals that guilty knowledge, relevant stimuli, and system knowledge all lead to increased use of countermeasures. The implications and limitations of this research are discussed and avenues for future research are outline

Credibility of Cyber Threat Communication on Twitter – Expert Evaluation of Indicators for Automated Credibility Assessment

Computer Emergency Response Teams (CERTs) are experts responsible for managing cybersecurity incidents. To identify cyber threats, they consider a wide range of sources from official vulnerability databases to public sources such as Twitter, which has an active cybersecurity community. Due to the high number of topic-related tweets per day, credibility assessment represents an immense effort in the daily work of CERTs. Although approaches for automated credibility assessment have already been developed in previous research, these mainly take peripheral cues into account, although users with domain expertise and a high level of personal involvement also assess content-related cues. We therefore conducted interviews with CERT members to re-evaluate known indicators for automated credibility assessment from an expert perspective. In doing so, we contribute valuable insights to the development of automated approaches for credibility assessment targeting users with high domain knowledge and personal involvement

Design Principles for Special Purpose, Embodied, Conversational Intelligence with Environmental Sensors (SPECIES) Agents

As information systems increase their ability to gather and analyze data from the natural environment and as computational power increases, the next generation of human-computer interfaces will be able to facilitate more lifelike and natural interactions with humans. This can be accomplished by using sensors to non-invasively gather information from the user, using artificial intelligence to interpret this information to perceive users’ emotional and cognitive states, and using customized interfaces and responses based on embodied-conversational-agent (avatar) technology to respond to the user. We refer to this novel and unique class of intelligent agents as Special Purpose Embodied Conversational Intelligence with Environmental Sensors (SPECIES) agents. In this paper, we build on interpersonal communication theory to specify four essential design principles of all SPECIES agents. We also share findings of initial research that demonstrates how SPECIES agents can be deployed to augment human tasks. Results of this paper organize future research efforts in collectively studying and creating more robust, influential, and intelligent SPECIES agents

The Viability of Using Rapid Judgments as a Method of Deception Detection

Rapid Judgments (RJs) are quick assessments based on indirect verbal and nonverbal cues that are known to be associated with deception. RJs are advantageous because they eliminate the need for expensive detection equipment and only require minimal training for coders with relatively accurate judgments. Results of testing on two different datasets showed that trained coders were reliably making RJs after watching both long and short interaction segments but their judgments were not more accurate than the expert interviewers. The RJs did not discriminate between truth and deception as hypothesized. This raises more questions about the conditions under which making RJs from verbal and nonverbal cues achieves accurate detection of veracity.18 month embargo; published online: 25 January 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Phishing Training: A Preliminary Look at the Effects of Different Types of Training

In this paper, we present the preliminary results of an experiment conducted to observe the impact of the different training techniques to increase the likelihood of participants identifying and reporting phishing messages. Three different training approaches were used – general video/quiz training, just-in-time training with simulated phishing emails, and a leaderboard, which awarded users points for forwarding correct phishing messages and penalized them for incorrect ones. The experiment emulated a normal working day of an executive assistant of a manager in an organization. Each participant was expected to accomplish work tasks and respond to work-related emails while watching for and reporting phishing messages. We observed that both general training and the presence of a leaderboard decreased the propensity to click on a phishing message, while we found no effect for different types of just-in-time training

Employee Compensation and Advanced Manufacturing Technology

[Excerpt] The globalization of product markets has intensified competition in an increasingly wide array of industries, including automobiles, consumer electronics,steel, and computer chips to name just a few. In manufacturing as a whole during the last thirty years, productivity growth in the U.S. has lagged significantly behind that of Japan, Germany, Sweden, and many other industrialized countries. For example, between 1960 and 1985, the annual growth in manufacturing productivity (output per hour) was 2.7 percent in the U.S. compared with 8.0 percent in Japan. Unless this trend can be turned around, U.S. companies will find it increasingly difficult to compete in the world market

Benchmarking Aided Decision Making in a Signal Detection Task

Copyright © 2017 Human Factors and Ergonomics Society. Reprinted by permission of SAGE Publications.Objective: A series of experiments examined human operators’ strategies for interacting with highly (93%) reliable automated decision aids in a binary signal detection task. Background: Operators often interact with automated decision aids in a suboptimal way, achieving performance levels lower than predicted by a statistically ideal model of information integration. To better understand operators’ inefficient use of decision aids, we compared participants’ automation-aided performance levels with the predictions of seven statistical models of collaborative decision making. Method: Participants performed a binary signal detection task that asked them to classify random dot images as either blue or orange dominant. They made their judgments either unaided or with assistance from a 93% reliable automated decision aid that provided either graded (Experiments 1 and 3) or binary (Experiment 2) cues. We compared automation-aided performance with the predictions of seven statistical models of collaborative decision making, including a statistically optimal model and Robinson and Sorkin’s contingent criterion model. Results and Conclusion: Automation-aided sensitivity hewed closest to the predictions of the two least efficient collaborative models, well short of statistically ideal levels. Performance was similar whether the aid provided graded or binary judgments. Model comparisons identified potential strategies by which participants integrated their judgments with the aid’s. Application: Results lend insight into participants’ automation-aided decision strategies and provide benchmarks for predicting automation-aided performance levels

Automated Human Screening for Detecting Concealed Knowledge

Screening individuals for concealed knowledge has traditionally been the purview of professional interrogators investigating a crime. But the ability to detect when a person is hiding important information would be of high value to many other fields and functions. This dissertation proposes design principles for and reports on an implementation and empirical evaluation of a non-invasive, automated system for human screening. The screening system design (termed an automated screening kiosk or ASK) is patterned after a standard interviewing method called the Concealed Information Test (CIT), which is built on theories explaining psychophysiological and behavioral effects of human orienting and defensive responses. As part of testing the ASK proof of concept, I propose and empirically examine alternative indicators of concealed knowledge in a CIT. Specifically, I propose kinesic rigidity as a viable cue, propose and instantiate an automated method for capturing rigidity, and test its viability using a traditional CIT experiment. I also examine oculomotor behavior using a mock security screening experiment using an ASK system design. Participants in this second experiment packed a fake improvised explosive device (IED) in a bag and were screened by an ASK system. Results indicate that the ASK design, if implemented within a highly controlled framework such as the CIT, has potential to overcome barriers to more widespread application of concealed knowledge testing in government and business settings

Incorporating Spatial Data and GIS to Improve SEA of Land use Plans: Opportunities and Limitations: Case Studies in the Republic of Ireland

This research aimed at establishing whether spatial data and Geographic Information Systems (GIS) can contribute to Strategic Environmental Assessment (SEA). To achieve this, an integrated GISEA approach was developed and applied to a number of spatial planning SEAs in the Republic of Ireland. The practical applicability of the approach was examined, evaluating the potential benefits derived from using spatial data and GIS in SEA and assessing the potential barriers to an effective GIS use. The implementation of the SEA Directive incorporated a new dimension into plan-making by calling for the assessment of potential environmental effects that may derive from implementing a plan. The intrinsic spatial nature of land use plans poses specific requirements on the tools and assessment methods used. GIS – with their capacity to visually display and spatially assess information- have the potential to support SEA processes. Moreover, GIS tools can tackle the spatio-temporal dimensions that conventional assessment methods (e.g. matrices and checklists) fail to address. To explore the validity of these arguments, GISEA was applied to seven Irish development plans. These were supported by interviews with the planners and technicians involved, and through review of published SEA environmental reports. The case studies demonstrated that GIS can provide the mappable aspects of SEA; they facilitate the process by enhancing understanding of environmental and planning considerations, and improving the accuracy of assessments. These observations concur with published literature on the predicted benefits of applying GIS at various environmental assessment levels. Nevertheless, the results revealed that framework and procedural difficulties remain (e.g. institutional arrangements and technical data issues). These are more apparent at higher planning tiers and in certain SEA stages such as public participation. The contribution of GIS largely depends on scope for spatial information, availability and quality of relevant datasets, and willingness of involved organisations to facilitate data provision and disclosure. Therefore, formulation of spatially-specific land use plans and improved data accessibility and quality can contribute to an effective GIS use in SEA. Further research and practice are required to disclose the full potential of GISEA, but the work-placement aspect of this research has already had a direct impact on the level of GIS use in Irish SEA practice

Highlights of contractor initiatives in quality enhancement and productivity improvement

The NASA/Contractor Team efforts are presented as part of NASA's continuing effort to facilitate the sharing of quality and productivity improvement ideas among its contractors. This complilation is not meant to be a comprehensive review of contractor initiative nor does it necessarily express NASA's views. The submissions represent samples from a general survey, and were not edited by NASA. The efforts are examples of quality and productivity programs in private industry, and as such, highlight company efforts in individual areas. Topics range from modernization of equipment, hardware, and technology to management of human resources. Of particular interest are contractor initiatives which deal with measurement and evaluation data pertaining to quality and productivity performance