The Interplay of Information Processing, Mindfulness, and Affective State in Phishing Detection

2023 | International Conference on Information Systems | Citations: 0

Authors: Bera, Debalina; Kim, Dan

Abstract: This study investigates the effect of individuals' information processing modes ... Expand

Abstract: This study investigates the effect of individuals' information processing modes on phishing email detection mechanisms and accuracy. Drawing on the heuristic-systematic model of processing, mindful decision-making, and affect-and-persuasion literature, this study examines the antecedents (i.e., heuristic, systematic processing, general and domain mindfulness, and affective state) and behavioral consequences (i.e., detection accuracy) in phishing identification. Using a scenario-based survey experiment this study shows mindfulness and affectivity navigate information processing mechanisms, thus influence phishing detection accuracy. It aims to contribute to information security literature by examining novel associations between general, domain mindfulness and its effect on online users' information processing strategy and phishing detection accuracy. Furthermore, this study contributes to phishing training and awareness by identifying the function of cognitive-affective (affective states, trait mindfulness) and cognitive-behavioral (domain mindfulness) factors on the choice of information processing modes and phishing detection accuracy. Finally, the affective states might help improve the efficacy of automatic filters. Collapse

Topics: phishing mindfulness electronic mail email phishing data security

Methods: experiment survey partial least squares regression machine learning laboratory experiment

Theories: protection motivation theory

Boosting Benefits, Offsetting Obstacles – the Impact of Explanations on AI Users’ Task Performance

2023 | International Conference on Business Informatics | Citations: 0

Authors: Walter, Marie Christine; Broder, Hanna Rebecca; Förster, Maximilian

Abstract: Artificial Intelligence (AI) bears the potential to inform human decision-makin ... Expand

Abstract: Artificial Intelligence (AI) bears the potential to inform human decision-making in a large variety of domains. However, its "black box" character poses an obstacle to human agency in interaction with AI-based decision support. A possible solution comes from the research field of Explainable AI (XAI), which generates explanations that reveal AI's functioning to users. Our research on XAI focuses on understanding the immediate and prolonged effect of XAIbased decision support on task performance. To this end, we conducted a randomized between-subjects online experiment with 289 participants performing the task of image classification. We find that explanations along AI decisions boost the positive effect of AI-based decision support on task performance during interaction. Furthermore, explanations can counterbalance the potential negative effect on prolonged task performance, which manifests after AI-based decision support is being withdrawn. Our findings contribute to understanding the impact of XAI on the outcome of human-AI interaction. Collapse

Topics: artificial intelligence task productivity decision support explainable artificial intelligence decision support system

Methods: experimental group experiment Mann Whitney U test nonparametric test statistical hypothesis test

Human or AI? Using Digital Behavior to Verify Essay Authorship

2023 | International Conference on Information Systems | Citations: 0

Authors: Wilson, David; Burnett, Parker; Valacich, Joseph; Jenkins, Jeff

Abstract: ... Expand

Abstract: Collapse

Topics: systems design artificial intelligence JavaScript systems evaluation deception detection

Methods: design artifact chatGPT design science experiment design requirement

A deep learning approach for detecting fake reviewers: Exploiting reviewing behavior and textual information

2023 | Decision Support Systems | Citations: 0

Authors: Zhang, Dong; Li, Wenwen; Niu, Baozhuang; Wu, Chong

Abstract: Ensuring the credibility of online consumer reviews (OCRs) is a growing societal ... Expand

Abstract: Ensuring the credibility of online consumer reviews (OCRs) is a growing societal concern. However, the problem of fake reviewers on online platforms significantly influences e-commerce authenticity and consumer trust. Existing studies for fake reviewer detection mainly focus on deriving novel behavioral and linguistic features. These features require extensive human labor and expertise, placing a heavy burden on platforms. Therefore, we propose a novel end-to-end framework to detect fake reviewers based on behavior and textual information. It has two key components: (1) a behavior-sensitive feature extractor that learns the underlying patterns of reviewing behavior; (2) a context-aware attention mechanism that extracts valuable features from online reviews. We rigorously evaluate each proposed module and the entire framework against state-of-the-art benchmarks on two real-world datasets from http://Yelp.com. Experimental results demonstrate that our method achieves state-ofthe-art results on fake reviewer detection. Our method can be considered a tentative step toward lowering human labor costs in realizing automated fake reviewer detection on e-commerce platforms. Collapse

Topics: fake review online review electronic commerce deception detection shapley additive explanation

Methods: machine learning digital trace data experiment parametric test deep learning

Trust and Distrust Network in Group Deception: An Exploratory study

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Ge, Saiying

Abstract: To investigate group deception and demote insider threats, this study leverages ... Expand

Abstract: To investigate group deception and demote insider threats, this study leverages network analysis to build a ranking of individuals' trustworthiness. Based on a large-scale, international experiment derived from an adversarial group game, we constructed directed unweighted social networks to analyze the dynamic trust and distrust interaction between individuals. By utilizing orally addressed positive and negative opinions, the networks capture the shifting of trustworthiness. As the outcome of collective group intelligence, the results support that node trustworthiness scores indicate actual trustworthiness. We also show that deception outcomes moderate the relationship between deception and node trustworthiness scores. This study contributes to the growing body of computational methods applied to trust in information systems, providing insights into deception and deception detection in small group contexts. Collapse

Topics: social network deception detection insider threat data encryption

Methods: computational algorithm network analysis experiment survey linear regression analysis

Improving Phishing Reporting Using Security Gamification

2022 | Journal of Management Information Systems | Citations: 2

Authors: Jensen, Matthew L.; Wright, Ryan T.; Durcikova, Alexandra; Karumbaiah, Shamya

Abstract: Phishing is an increasing threat that causes billions in losses and damage to pr ... Expand

Abstract: Phishing is an increasing threat that causes billions in losses and damage to productivity, trade secrets, and reputations each year. This work explores how security gamification techniques can improve phishing reporting. We contextualized the cognitive evaluation theory (CET) as a kernel theory and constructed a prototype phishing reporting system. With three experiments in a simulated work setting, we tested gamification elements of validation, attribution, incentives, and public presentation for improvements in experiential (e.g., motivation) and instrumental outcomes (e.g., hits and false positives) in phishing reporting. Our findings suggest public attribution with rewards and punishments best balance the competing necessities of accuracy with widespread reporting. Furthermore, our results demonstrate the unique benefits of security gamification to phishing reporting over and above other phishing mitigation techniques (e.g., training and warnings). However, we also noted that unintended consequences in false alarms might arise from shifts in motivation resulting from public display of incentives. These findings suggest that carefully calibrated external incentives (rather than intrinsic rewards) are most likely to improve the ancillary task of phishing reporting. Collapse

Topics: phishing gamification productivity self efficacy electronic mail

Methods: experiment factorial experiment multivariate analysis of covariance survey design artifact

Theories: cognitive evaluation theory

Explaining consumer suspicion: insights of a vignette study on online product reviews

2022 | Electronic Markets | Citations: 4

Authors: Kollmer, Tim; Eckhardt, Andreas; Reibenspiess, Victoria

Abstract: As part of the online product and service selection and purchase process, many c ... Expand

Abstract: As part of the online product and service selection and purchase process, many consumers consult and rely on online product reviews. In order to persuade potential customers to buy their products, many organizations and businesses post deceptive product reviews of their own products on their own or third-party websites to their advantage. This creates consumer suspicion about the authenticity and veracity of online product reviews. To better understand how consumers’ experiences of having been deceived by deceptive online product reviews in the past and the density of deception characteristics in an online product review influence their level of suspicion about the review and, ultimately, their intention to buy the product, we conduct a 3 × 3 vignette study. Our results indicate that deceptive characteristics in online product reviews and prior encounters with deception in online marketplaces increase consumer suspicion. Furthermore, we show that preference for a specific product decreases consumer suspicion about reviews of that product. Lastly, we demonstrate that consumer suspicion towards a product decreases purchase intention. Collapse

Topics: online review electronic market deception detection electronic commerce data accuracy

Methods: product review experiment survey regression analysis method descriptive statistic

Theories: interpersonal deception theory

Unleashing the Potential of Argument Mining for IS Research: A Systematic Review and Research Agenda

2022 | International Conference on Information Systems | Citations: 0

Authors: Weingart, Pablo; Wambsganss, Thiemo; Söllner, Matthias

Abstract: Argument mining (AM) represents the unique use of natural language processing ( ... Expand

Abstract: Argument mining (AM) represents the unique use of natural language processing (NLP) techniques to extract arguments from unstructured data automatically. Despite expanding on commonly used NLP techniques, such as sentiment analysis, AM has hardly been applied in information systems (IS) research yet. Consequentially, knowledge about the potentials for the usage of AM on IS use cases appears to be still limited. First, we introduce AM and its current usage in fields beyond IS. To address this research gap, we conducted a systematic literature review on IS literature to identify IS use cases that can potentially be extended with AM. We develop eleven text-based IS research topics that provide structure and context to the use cases and their AM potentials. Finally, we formulate a novel research agenda to guide both researchers and practitioners to design, compare and evaluate the use of AM for text-based applications and research streams in IS. Collapse

Topics: information system use database system data security IT security electronic commerce

Methods: natural language processing structured literature research literature sample literature study sentiment analysis

Customer perception of the deceptiveness of online product reviews: A speech act theory perspective

2021 | International Journal of Information Management | Citations: 6

Authors: Ansari, Sana; Gupta, Sumeet

Abstract: With the presence of fake reviews on e-commerce platforms, the reliability of re ... Expand

Abstract: With the presence of fake reviews on e-commerce platforms, the reliability of reviews becomes questionable. The extant literature demonstrates the impact of fake reviews on product sales and proposes several algorithms to prevent fake reviews from being displayed on the platform. However, what has largely remained uninvestigated is how customers perceive reviews present on the e-commerce platform. Based on the speech act theory, we develop a theoretical framework that explains how the linguistic style (both at the word and the structural level) acts as a cue for assessing a reviewer’s (in)sincere intentions. We evaluate the framework on a corpus of 120 online product reviews – each examined by at least 50 customers – using the fractional logit model. Results suggest that the communication style of a speaker reflects his/her intention. Reviews with less contextual embedding, argument structuring, and flattering through non-verbal cues trigger customers towards perceiving a review as deceptive. Collapse

Topics: online review mobile phone electronic commerce user-generated content electronic mail

Methods: survey survey design computational algorithm descriptive statistic parametric test

Theories: speech act theory

Design Thinking for Cyber Deception

2021 | HICSS | Citations: 0

Authors: Ashenden, Debi; Black, Rob; Reid, Iain; Henderson, Simon

Abstract: Cyber deception tools are increasingly sophisticated but rely on a limited set o ... Expand

Abstract: Cyber deception tools are increasingly sophisticated but rely on a limited set of deception techniques. In current deployments of cyber deception, the network infrastructure between the defender and attacker comprises the defence/attack surface. For cyber deception tools and techniques to evolve further they must address the wider attack surface; from the network through to the physical and cognitive space. One way of achieving this is by fusing deception techniques from the physical and cognitive space with the technology development process. In this paper we trial design thinking as a way of delivering this fused approach. We detail the results from a design thinking workshop conducted using deception experts from different fields. The workshop outputs include a critical analysis of design provocations for cyber deception and a journey map detailing considerations for operationalising cyber deception scenarios that fuse deception techniques from other contexts. We conclude with recommendations for future research. Collapse

Topics: design thinking deception detection data encryption IT security systems development

Methods: design methodology design artifact