Developing a measure of adversarial thinking in social engineering scenarios

Social engineering is a major issue for organizations. In this paper, we propose that increasing adversarial thinking can improve individual resistance to social engineering attacks. We formalize our understanding of adversarial thinking using Utility Theory. Next a measure of adversarial thinking in a text-based context. Lastly the paper reports on two studies that demonstrate the effectiveness of the newly developed measure. We show that the measure of adversarial thinking has variability, can be manipulated with training, and that it is not influenced significantly by priming. The paper also shows that social engineering training has an influence on adversarial thinking and that practicing against an adversarial conversational agent has a positive influence on adversarial thinking

The effect of conversational agent skill on user behavior during deception

Conversational agents (CAs) are an integral component of many personal and business interactions. Many recent advancements in CA technology have attempted to make these interactions more natural and human-like. However, it is currently unclear how human-like traits in a CA impact the way users respond to questions from the CA. In some applications where CAs may be used, detecting deception is important. Design elements that make CA interactions more human-like may induce undesired strategic behaviors from human deceivers to mask their deception. To better understand this interaction, this research investigates the effect of conversational skill—that is, the ability of the CA to mimic human conversation—from CAs on behavioral indicators of deception. Our results show that cues of deception vary depending on CA conversational skill, and that increased conversational skill leads to users engaging in strategic behaviors that are detrimental to deception detection. This finding suggests that for applications in which it is desirable to detect when individuals are lying, the pursuit of more human-like interactions may be counter-productive

Facilitating Natural Conversational Agent Interactions: Lessons from a Deception Experiment

This study reports the results of a laboratory experiment exploring interactions between humans and a conversational agent. Using the ChatScript language, we created a chat bot that asked participants to describe a series of images. The two objectives of this study were (1) to analyze the impact of dynamic responses on participants’ perceptions of the conversational agent, and (2) to explore behavioral changes in interactions with the chat bot (i.e. response latency and pauses) when participants engaged in deception. We discovered that a chat bot that provides adaptive responses based on the participant’s input dramatically increases the perceived humanness and engagement of the conversational agent. Deceivers interacting with a dynamic chat bot exhibited consistent response latencies and pause lengths while deceivers with a static chat bot exhibited longer response latencies and pause lengths. These results give new insights on social interactions with computer agents during truthful and deceptive interactions

Examining the learning effects of live streaming video game instruction over Twitch

Technology facilitates advances in learning and drives learning paradigms. One recent innovation is Twitch™, an online streaming platform often used for video game tutorials but also enables amateur online instruction (Hamilton, Garretson, & Kerne, 2014)). Twitch represents a unique learning paradigm that is not perfectly represented in previous technologies because of its “ground-up” evolution and the opportunity for novice instructors to educate mass audiences in real-time over the Internet while enabling interaction between teachers and learners and among learners. The purpose of this research is to empirically examine the efficacy of Twitch as a learning platform by manipulating each of the key characteristics of Twitch and to understand the conditions in which novice instructors may be beneficial. Drawing from Cognitive Load Theory, we demonstrate the worked-example effect in the Twitch environment by manipulating teacher-learner-learner interactions, live versus recorded streaming, and expert-versus novice-based instruction. Based on a laboratory experiment involving 350 participants, we found that learning performance under novice instructors was at least as good as that of experts. However, an exploratory analysis of learner personalities revealed that extroverts benefit only when learner-learner interaction is enabled. Surprisingly, those who are highly agreeable and less neurotic benefited more from novice instructors

Trends in Phishing Attacks: Suggestions for Future Research

One of the most common and costly forms of deception and fraud online is phishing. Due to the ramifications of successfulphishing attacks, security experts and researchers seek to better understand this phenomenon. Prior phishing research hasaddressed the “bait” and “hook” components of phishing attacks, the human-computer interaction that takes place as usersjudge the veracity of phishing emails and websites, and the development of technologies that can aid users in identifying andrejecting these attacks. Despite the extant research on this topic, phishing attacks continue to be successful as tactics evolve,rendering existing research less relevant. Although numerous tools have been created to aid people in recognizing phishingattacks, users disregard the recommendations of these tools. This paper summarizes the core of phishing research, providesan update on trending attack methods, and proposes future research addressing computer credibility in a phishing context

The Influence of Conversational Agents on Socially Desirable Responding

Conversational agents (CAs) are becoming an increasingly common component in many information systems. The ubiquity of CAs in cell phones, entertainment systems, and messaging applications has led to a growing need to understand how design choices made when developing CAs influence user interactions. In this study, we explore the use case of CAs that gather potentially sensitive information from people-”for example, in a medical interview. Using a laboratory experiment, we examine the influence of CA responsiveness and embodiment on the answers people give in response to sensitive and non-sensitive questions. The results show that for sensitive questions, the responsiveness of the CA increased the social desirability of the responses given by participants

Is Trust Always Better than Distrust? The Potential Value of Distrust in Newer Virtual Teams Engaged in Short-term Decision-Making

The debate on the benefits of trust or distrust in groups has generated a substantial amount of research that points to the positive aspects of trust in groups, and generally characterizes distrust as a negative group phenomenon. Therefore, many researchers and practitioners assume that trust is inherently good and distrust is inherently bad. However, recent counterintuitive evidence obtained from face-to-face (FtF) groups indicates that the opposite might be true; trust can prove detrimental, and distrust instrumental, to decision-making in groups. By extending this argument to virtual teams (VTs), we examined the value of distrust for VTs completing routine and non-routine decision tasks, and showed that the benefits of distrust can extend to short-term VTs. Specifically, VTs seeded with distrust significantly outperformed all control groups in a non-routine decision-making task. In addition, we present quantitative evidence to show that the decision task itself can significantly affect the overall levels of trust/distrust within VTs. In addition to its practical and research implications, the theoretical contribution of our study is that it extends to a group level, and then to a VT setting, a theory of distrust previously tested in the psychology literature in the context of completing non-routine and routine decision tasks at an individual level

The influence of conversational agent embodiment and conversational relevance on socially desirable responding

Conversational agents (CAs) are becoming an increasingly common component in a wide range of information systems. A great deal of research to date has focused on enhancing traits that make CAs more humanlike. However, few studies have examined the influence such traits have on information disclosure. This research builds on self-disclosure, social desirability, and social presence theories to explain how CA anthropomorphism affects disclosure of personally sensitive information. Taken together, these theories suggest that as CAs become more humanlike, the social desirability of user responses will increase. In this study, we use a laboratory experiment to examine the influence of two elements of CA design—conversational relevance and embodiment—on the answers people give in response to sensitive and non-sensitive questions. We compare the responses given to various CAs to those given in a face-to-face interview and an online survey. The results show that for sensitive questions, CAs with better conversational abilities elicit more socially desirable responses from participants, with a less significant effect found for embodiment. These results suggest that for applications where eliciting honest answers to sensitive questions is important, CAs that are “better” in terms of humanlike realism may not be better for eliciting truthful responses to sensitive questions

Overview and Guidance on Agile Development in Large Organizations

A continual debate surrounds the effectiveness of agile software development practices. Some organizations adopt agile practices to become more competitive, improve processes, and reduce costs. Other organizations are skeptical about whether agile development is beneficial. Large organizations face an additional challenge in integrating agile practices with existing standards and business processes. To examine the effects of agile development practices in large organizations, we review and integrate scientific literature and theory on agile software development. We further organize our theory and observations into a framework with guidelines for large organizations considering agile methodologies. Based on this framework, we present recommendations that suggest ways large organizations with established processes can successfully implement agile practices. Our analysis of the literature and theory provides new insight for researchers of agile software development and assists practitioners in determining how to adopt agile development in their organizations

Establishing a Foundation for Automated Human Credibility Screening

Automated human credibility screening is an emerging research area that has potential for high impact in fields as diverse as homeland security and accounting fraud detection. Systems that conduct interviews and make credibility judgments can provide objectivity, improved accuracy, and greater reliability to credibility assessment practices, need to be built. This study establishes a foundation for developing automated systems for human credibility screening