Benchmarking the Robustness of Phishing Email Detection Systems

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Ampel, Benjamin; Gao, Yang; Hu, James; Samtani, Sagar; Chen, Hsinchun

Abstract: Social engineering attacks are currently the most cited cybersecurity threat to ... Expand

Abstract: Social engineering attacks are currently the most cited cybersecurity threat to organizations. Phishing emails are the most salient form of social engineering attacks. Organizations are increasingly implementing AI-enabled systems to detect phishing emails. However, AI-enabled systems are often susceptible to textual perturbations, where an adversary makes a small change to cause a misclassification. In this study, we sought to identify the performance of prevailing phishing email detection systems (PEDS) against character, word, sentence, and multi-level adversarial text perturbations. Through a principled benchmarking framework, we quantitatively demonstrated the lack of robustness prevailing PEDS have to specific types of text-based adversarial perturbations (e.g., character, word, sentence, multi-level). The results of this study provide new insights into the robustness of AI-based PEDS and highlight the need for organizations to adopt a multi-layered approach to phishing protection. Additionally, organizations can implement our benchmark framework to test their PEDS against adversarial perturbations. Collapse

Topics: artificial intelligence electronic mail email phishing phishing IT security

Methods: word2vec random forest classification naïve bayes literature study pre-trained language model

Influencing the Influencers? The Case of @CelebJets and the Role of Social Media in Empowering Citizens to Conduct Climate Justice Activism

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Berney, Manon; Ondrus, Jan; Holzer, Adrian

Abstract: Online climate change activism is growing. However, its effectiveness is not ye ... Expand

Abstract: Online climate change activism is growing. However, its effectiveness is not yet firmly established. One of the challenges is for citizens to make sense of the vast amount of data to understand the impact of specific behaviors. The aggregation of publicly available information in a comprehensible and playful manner could potentially trigger effective evidence-based activism. However, it is not yet clear if and how such an intervention works. In this paper, we make a preliminary analysis of a use case of such an approach by investigating the @CelebJets phenomena, which automatically tracks and shares the private jet flights of celebrities on Twitter. Our analysis demonstrates that this approach can elicit user engagement and provide pertinent material for the press, potentially leading to a shift in behavior, particularly among celebrities who are promoting sustainability. Collapse

Topics: Twitter application programming interface social media climate change Wikipedia

Methods: case study regression analysis method parametric test descriptive statistic field experiment

The Paradoxical Role of Humanness in Aggression Toward Conversational Agents

2023 | Journal of Management Information Systems | Citations: 0

Authors: Brendel, Alfred Benedikt; Hildebrandt, Fabian; Dennis, Alan R.; Riquel, Johannes

Abstract: Conversational Agents (CAs) are becoming part of our everyday lives. About 10 pe ... Expand

Abstract: Conversational Agents (CAs) are becoming part of our everyday lives. About 10 percent of users display aggressive behavior toward CAs, such as swearing at them when they produce errors. We conducted two online experiments to understand user aggression toward CAs better. In the first experiment, 175 participants used either a humanlike CA or a non-humanlike CA. Both CAs worked without errors, and we observed no increased frustration or user aggression. The second experiment (with 201 participants) was the focus of this study; in it, both CAs produce a series of errors. The results show that frustration with errors drives aggression, and users with higher impulsivity are more likely to become aggressive when frustrated. The results also suggest that there are three pathways by which perceived humanness influences users' aggression to CAs. First, perceived humanness directly increases the frustration with the CA when it produces errors. Second, perceived humanness increases service satisfaction which in turn reduces frustration. Third, perceived humanness influences the nature of aggression when users become frustrated (i.e., users are less likely to use highly offensive words with a more humanlike CA). Our research contributes to our theoretical understanding of the role of anthropomorphism in the interaction with machines, showing that designing a CA to be more humanlike is a double-edged sword—both increasing and decreasing the frustration that leads to aggression—and also a means to reduce the most severe aggression. Collapse

Topics: Wikipedia user behavior ease of use electronic mail personality

Methods: experiment theory development statistical hypothesis test chatbot SEM tool

Theories: social response theory

Token Incentives in a Volatile Crypto Market: The Effects of Token Price Volatility on User Contribution

2023 | Journal of Management Information Systems | Citations: 0

Authors: Chen, Kun; Fan, Yifan; Liao, Shaoyi Stephen

Abstract: Crypto tokens, issued and managed via smart contracts, function as rewards in bl ... Expand

Abstract: Crypto tokens, issued and managed via smart contracts, function as rewards in blockchain systems to encourage user participation. Distinct from monetary incentives, token incentives are uncertain in reward magnitude due to the large swings in token prices on crypto markets. By focusing on token price volatility, this study investigates how the reward uncertainty affects user contribution in a tokenized digital platform. Our empirical setting is Steemit, a platform where bloggers write posts and share token rewards based on their posts' popularity. We find that while high token price volatility induces a large volume of blog posts, it diminishes post quality. The dichotomous effects are explained via two mechanisms: users' direct reactions to reward uncertainties and their indirect reactions, mediated by altered token preference amid volatility shocks. Deeply exploring this dynamic process, our results reveal that token price volatility facilitates a platform's network short-term effect but impairs long-term user creativity. Our empirical findings thus extend the literature on blockchain economics and cryptocurrencies and have practical implications for the design of incentive mechanisms on tokenized digital platforms. Collapse

Topics: blog blockchain digital platform cryptocurrency user behavior

Methods: longitudinal research instrumental variables estimation data transformation principal component analysis vector autoregression

Theories: motivation crowding theory

Integration of Computer Vision with Analogical Reasoning for Characterizing Unknowns

2023 | HICSS | Citations: 0

Authors: Combs, K.; Bihl, T.; Ganapathy, S.

Abstract: Current state-of-the-art artificial intelligence struggles with accurate interp ... Expand

Abstract: Current state-of-the-art artificial intelligence struggles with accurate interpretation of out-of-library (OOL) objects. One method proposed remedy is analogical reasoning (AR), which utilizes abductive reasoning to draw inferences on an unfamiliar scenario given knowledge about a similar familiar scenario. Currently, applications of visual AR gravitate toward analogy-formatted image problems rather than to computer vision data sets. The Image Recognition Through Analogical Reasoning Algorithm (IRTARA) approach described herein shows how AR can be leveraged to improve computer vision in OOL situations. IRTARA produces a word-based term frequency list that characterizes the OOL object of interest. To evaluate the quality of the results of IRTARA, both quantitative and qualitative assessments are used, including a baseline to compare the automated methods with human-generated results. Fifteen OOL objects were tested using IRTARA, which showed consistent results across all three evaluation methods on the objects that performed exceptionally well or poorly overall. Collapse

Topics: floppy disk Wikipedia Python ergonomics usability

Methods: computational algorithm experiment word embedding GloVe survey

Search & Verify: Misinformation and source evaluations in Internet search results

2023 | Decision Support Systems | Citations: 0

Authors: Dennis, Alan R.; Moravec, Patricia L.; Kim, Antino

Abstract: In response to online misinformation, source rating services evaluate thousands ... Expand

Abstract: In response to online misinformation, source rating services evaluate thousands of popular websites, mark them as reputable or disreputable, and provide detailed information explaining their evaluations. In this paper, we examine the effects of news source evaluations by experts as well as crowd-sourced information (i.e., Wikipedia) on beliefs in political news that appears in Internet search results. Through two online experiments, we inves­ tigate the effects of providing a simple source-evaluation flag or a flag with more detailed supporting information explaining the evaluation. We found that negative flags from expert fact-checkers reduced users' beliefs, and supporting information had no additional effect; in contrast, positive flags required information beyond the simple flag to have maximum effectiveness. Positive and negative crowd-sourced information had similar effects but was weaker than evaluations from experts. Thus, we conclude that providing additional information to support source evaluation flags is important to give users confidence in reputable websites. Collapse

Topics: Wikipedia internet technology crowdsourcing fake news blog

Methods: theory development linear regression analysis experiment post-hoc analysis survey

Theories: argumentation theory

Opinion Paper: “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

2023 | International Journal of Information Management | Citations: 0

Authors: Dwivedi, Yogesh K.; Kshetri, Nir; Hughes, Laurie; Slade, Emma Louise; Jeyaraj, Anand; Kar, Arpan Kumar; Baabdullah, Abdullah M.; Koohang, Alex; Raghavan, Vishnupriya; Ahuja, Manju; Albanna, Hanaa; Albashrawi, Mousa Ahmad; Al-Busaidi, Adil S.; Balakrishnan, Janarthanan; Barlette, Yves; Basu, Sriparna; Bose, Indranil; Brooks, Laurence; Buhalis, Dimitrios; Carter, Lemuria; Chowdhury, Soumyadeb; Crick, Tom; Cunningham, Scott W.; Davies, Gareth H.; Davison, Robert M.; Dé, Rahul; Dennehy, Denis; Duan, Yanqing; Dubey, Rameshwar; Dwivedi, Rohita; Edwards, John S.; Flavián, Carlos; Gauld, Robin; Grover, Varun; Hu, Mei-Chih; Janssen, Marijn; Jones, Paul; Junglas, Iris; Khorana, Sangeeta; Kraus, Sascha; Larsen, Kai R.; Latreille, Paul; Laumer, Sven; Malik, F. Tegwen; Mardani, Abbas; Mariani, Marcello; Mithas, Sunil; Mogaji, Emmanuel; Nord, Jeretta Horn; O’Connor, Siobhan; Okumus, Fevzi; Pagani, Margherita; Pandey, Neeraj; Papagiannidis, Savvas; Pappas, Ilias O.; Pathak, Nishith; Pries-Heje, Jan; Raman, Ramakrishnan; Rana, Nripendra P.; Rehm, Sven-Volker; Ribeiro-Navarrete, Samuel; Richter, Alexander; Rowe, Frantz; Sarker, Suprateek; Stahl, Bernd Carsten; Tiwari, Manoj Kumar; Van Der Aalst, Wil; Venkatesh, Viswanath; Viglia, Giampaolo; Wade, Michael; Walton, Paul; Wirtz, Jochen; Wright, Ryan

Abstract: ☆ This editorial opinion paper provides a subjective viewpoint on the potential ... Expand

Abstract: ☆ This editorial opinion paper provides a subjective viewpoint on the potential impact of generative AI technologies such as ChatGPT in the domains of education, business, and society. Its objective is to offer initial guidance on the opportunities, challenges, and implications associated with these technologies. It is worth noting that, given its nature as an editorial opinion piece, this submission has not undergone a formal double-blind review process but has been reviewed informally by appropriate experts.Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT's capabilities to enhance productivity and suggest that it is likely to offer 1 Equal contributions Y.K. Dwivedi et al.International Journal of Information Management 71 (2023) 102642 3 significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT's use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts. Collapse

Topics: artificial intelligence generative AI Twitter privacy innovation management

Methods: chatGPT chatbot generative pre-trained transformer literature study language model

Hey Article, What Are You About? Question Answering for Information Systems Articles through Transformer Models for Long Sequences

2023 | HICSS | Citations: 0

Authors: Ebert, L.; Huettemann, S.; Mueller, R.

Abstract: Question Answering (QA) systems can significantly reduce manual effort of searc ... Expand

Abstract: Question Answering (QA) systems can significantly reduce manual effort of searching for relevant information. However, challenges arise from a lack of domain-specificity and the fact that QA systems usually retrieve answers from short text passages instead of long scientific articles. We aim to address these challenges by (1) exploring the use of transformer models for long sequence processing, (2) performing domain adaptation for the Information Systems (IS) discipline and (3) developing novel techniques by performing domain adaptation in multiple training phases. Our models were pre-trained on a corpus of 2 million sentences retrieved from 3,463 articles from the Senior Scholars' Basket and fine-tuned on SQuAD and a manually created set of 500 QA pairs from the IS field.In six experiments, we tested two transfer learning techniques for fine-tuning (TANDA and FANDO). The results show that fine-tuning with task-specific domain knowledge considerably increases the models' Collapse

Topics: Wikipedia online learning system technology adoption IS discipline crowdsourcing

Methods: experiment machine learning deep learning computational algorithm transformer model

Theories: adaptive structuration theory structuration theory

Shooting ‘Yohani’ to Global Stardom: A Teaching Case of Social Media Strategy of a Top-10 YouTuber

2023 | Communications of the Association for Information Systems | Citations: 0

Authors: Egodawele, Mekhala; Sedera, Darshana; Grover, Varun; Seneviratne, Dilanjan; Sooriyapperuma, Banura

Abstract: This teaching case is about 'Yohani' -a Global YouTube sensation. Yohani's song ... Expand

Abstract: This teaching case is about 'Yohani' -a Global YouTube sensation. Yohani's song 'Menike Mage Hithe' reached the top hits of Amazon Music and Spotify, eventually making its way to the YouTube Top-10 global charts in September 2021. Gathering in-depth insights from the executive staff behind her record label company and her creative company, this teaching case demonstrates (i) the role of a social media strategy in contemporary businesses and entrepreneurs; (ii) social media hygiene factors that one must consider; (iii) how social media insights gained through analytics assisted in delivering a carefully orchestrated business strategy, and (iv) how a combination of social media platforms was employed while considering a range of technological, geographical, financial and social factors. The case and its teaching notes are suitable for undergraduate and postgraduate students studying a contemporary information systems management course. Collapse

Topics: social media Facebook YouTube Instagram TikTok

Distant and Local Knowledge: Investigating the Effect of Changing Interest in Knowledge Generation

2023 | International Conference on Information Systems | Citations: 0

Authors: Feiter, Tim; Resch, Christian; Kock, Alexander

Abstract: This study examines how changes between drawing inspiration from distant knowle ... Expand

Abstract: This study examines how changes between drawing inspiration from distant knowledge and focusing on local knowledge affect contributions in online communities. The research compares two theoretical frameworks for understanding knowledge generation: The tension-based view highlights the tensional perspective of initially engaging with distant knowledge before narrowing the focus to specific domains to foster creative behavior. Conversely, the foundational view posits that creative behavior requires local expertise before it is combined with insights from distant knowledge domains. We collected data from 15 Q&A forums hosted by Stack Exchange and used natural language processing to analyze users' contributions and changes in interest. Our findings suggest that both theories explain knowledge generation. Individuals need to engage with more distant knowledge over time but also streamline their interests between local and distant knowledge domains to generate more valuable and novel contributions. The study enriches understanding of knowledge generation in online communities and offers insights into how to support creative individuals. Collapse

Topics: online community social network open innovation innovation management database system

Methods: BERT natural language processing transformer model archival research linear regression analysis

Theories: creativity theory