AIS Transactions on Enterprise Systems

Beyond Phishing: Detecting MFA Fatigue and Adversary-in-the-Middle at Scale

2025-09-09T07:15:30+00:00

This study proposes a defender-centric strategy to detect and contain two fast-rising attack patterns—MFA fatigue and Adversary-in-the-Middle (AiTM)—without relying on expensive tooling. We introduce a lightweight pipeline that fuses identity telemetry (push frequency anomalies, impossible travel), web gateway indicators (suspicious reverse-proxy domains), and endpoint signals (token theft heuristics) into actionable detections. Evaluated across 15 small-to-medium organizations, the approach reduced median time-to-detect by 63% and cut successful account takeovers by 41% over eight weeks. We document failure modes (e.g., noisy travel baselines), provide hardening tips (phishing-resistant MFA, conditional access, token binding), and publish query patterns that can be adapted to common SIEM/XDR platforms. The results indicate that defenders can meaningfully blunt modern phishing and session-hijacking campaigns with modest engineering effort and targeted telemetry enrichment.

Beyond Phishing: Detecting MFA Fatigue and Adversary-in-the-Middle at Scale

2025-09-09T04:38:12+00:00

Beyond Phishing: Detecting MFA Fatigue and Adversary-in-the-Middle at Scale

2025-09-05T14:42:44+00:00

The Relationship of Computer Aptitude, Positive Affect, and Openness Personality Traits on Learning Enterprise Systems

2024-03-27T15:24:33+00:00

Enterprise Resource Planning (ERP) systems are complex enterprise information systems. They are the backbone for running most enterprises and support integrated business processes across the supply chain, including sales and distribution, materials management, financial accounting, and managerial accounting processes. The need for individuals who can learn to use these systems successfully is a recurring challenge and is a talent acquisition priority for organizations. This research seeks to explore the relationships between computer aptitude, Positive Affect, and the Openness personality trait in the successful learning of ERP systems. Structural equation modeling was used to test the research hypotheses. The results revealed that users’ cognitive aptitude for computing and Positive Affect were positively related to their ERP system learning performance. Furthermore, users’ Openness personality trait was positively related to their Positive Affect.

Success Factors in Efficient Mergers & Acquisitions Activities:

2023-01-17T10:04:47+00:00

In 2021, the global mergers & acquisitions (M&A) market remained strong, with transaction volumes reaching $5.9 trillion and an increasing number of large deals. Despite the strategic impact and the high priority of every transaction, many of them fail to deliver the anticipated value due to inferior implementation, both from a post-merger IT integration (IT PMI) and an IT carve-out perspective. This paper explains how one of the world’s largest engineering companies (TURBO) has developed IT M&A capabilities to ensure both efficient post-merger IT-PMI and IT-carve-out projects. Their key to success relies on two principles, (1) standardization of the IT integration and respectively IT separation (carve-out) process, and (2) standardization of the enterprise architecture. By establishing these principles, TURBO managed to reduce both time and costs of its IT integration and IT carve-out projects by on average 40 %. Based on this case study, the paper synthesizes four success factors that can inform managers of M&A active organizations to successfully build IT-PMI and IT-carve-out capabilities.

On the Journey to AI Maturity

2022-02-27T17:10:03+00:00

Artificial Intelligence (AI) has recently become pivotal in day-to-day business. However, surveys show that underlying, systemic issues – aside from AI-related aspects – hinder its enterprise-wide adoption. In this study, we aim to understand the role of this new breed of providers on the path to AI maturity and enterprise-wide adoption. We collect secondary data (i.e., surveys) from 154 white papers published by companies implementing AI solutions and apply descriptive and thematic analysis to understand the current challenges and opportunities of AI implementation. The thematic analysis involves topic modelling using natural language-processing algorithms. Our results demonstrate that, despite AI service providers addressing – at least in part – the major challenges faced by clients, there is still a gap between the skills demanded by end-users, and skills possessed by and focused on AI service providers.

Studying Digital Initiatives: Applying Established Perspectives to Emerging Digital Phenomena

2021-06-18T14:56:18+00:00

The information systems (IS) discipline is witnessing a shift in topical areas due to an ever-growing pervasiveness of digital technologies. Digitalization is rapidly transforming the fabric and organizing logics of firms and has introduced new business practices and opportunities. To catch up with the digitalization wave, IS scholars have been exposing the IS literature to a plethora of brand-new phenomena and theories. While such a considerable topical shift toward fashionable topics is necessary to maintain the dynamics of the IS discipline, it may compromise the cumulative nature of knowledge development. In this paper, we afford a reflexive discussion on the use of existing established theories and research approaches in studying emerging digital phenomena. To this end, we demonstrate the use of stakeholder theory and a two-dimensional research approach, as exemplars of existing established research perspectives, to the topic of digital platforms, as one of the digital phenomena that has recently drawn the attention of IS scholars.

Design of a Neuronal Training Modeling Language

2021-03-05T10:59:33+00:00

As the complexity of learning task requirements, computer infrastructures and knowledge acquisition for artificial neuronal networks (ANN) is increasing, the communication about ANN is challenging. An efficient, transparent and failure-free design of learning tasks by models is not supported by any tool at all. For this purpose, particular the consideration of data, information, and knowledge on the base of an integration with knowledge-intensive business process models and a process-oriented knowledge management are attractive. With the aim of making the design of learning tasks expressible by models, this paper proposes a graphical modeling language called Neuronal Training Modeling Language (NTML), which allows the repetitive use of learning designs. An example ANN project of AI-based dynamic GUI adaption exemplifies its use as a first demonstration.

Embedding Robotic Process Automation into Process Management

2020-04-30T22:51:40+00:00

XYZ Company routinely faced penalties imposed by the United States Internal Revenue Service (IRS) for non-compliance in depositing federal withholding taxes related to the managed benefits plans for its clients. Since the rules for depositing the federal taxes were complex and differed between the benefits plans, it was common for XYZ Company to accrue penalties imposed by the IRS. Desiring to eliminate penalties by complying 100% with the IRS guidelines, XYZ Company considered various solutions. Finally, XYZ Company implemented a Robotic Process Automation (RPA) solution using the open source tool—taskt—to achieve 100% compliance in depositing federal withholding taxes and eliminate penalties. Discussion of solution improvements, reflection and next steps, technical challenges, lessons learned, and design science retrospective is provided.

An approach to model forgetting

2019-11-12T08:54:39+00:00

This paper aims to investigate the possibility to include aspects of forgetting into business process modeling. To date, there is no possibility to model forgotten or to-be- forgotten elements beyond the mere deletion. On a first attempt, we focus on the individual level and model knowledge transformation within a single person. Using the Knowledge Model Description Language, we propose ways to include different forms of forgetting into the realm of modeling tools. Using data from an experimental setting within an assembly line production environment, the usability of those new modeling tools is tested. So far, the applicability of modeling features for forgetting on the individual level is mostly restricted to a research context. However, clear requirements to transfer the tools onto the team- and organizational level are set out.