Benjamin M. Ampel
Benjamin M. Ampel
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2
Seeing Is Not Believing: A Deepfake Video Call Scam at Pan-Asia Trading
This teaching case examines a deepfake video call scam that targeted Pan-Asia Trading, illustrating the emerging cybersecurity threats …
Benjamin M. Ampel
Last updated on Feb 5, 2026
A Computational Design Framework for Targeted Disruption of Hacker Communities
This paper presents a computational design framework for the targeted disruption of hacker communities. By leveraging advanced …
Benjamin M. Ampel
Last updated on Feb 5, 2026
DOI
Automatically Detecting Voice Phishing: A Large Audio Model Approach
Voice phishing (vishing) attacks have become increasingly sophisticated, exploiting audio-based communication channels to deceive …
Benjamin M. Ampel
,
Sagar Samtani
,
Hsinchun Chen
Last updated on Feb 5, 2026
DOI
Large Language Models for Conducting Advanced Text Analytics Information Systems Research
The exponential growth of digital content has generated massive textual datasets, necessitating the use of advanced analytical …
Benjamin M. Ampel
,
Chi-Heng Yang
,
James Hu
,
Hsinchun Chen
Last updated on Feb 5, 2026
PDF
DOI
Creating Proactive Cyber Threat Intelligence with Hacker Exploit Labels: A Deep Transfer Learning Approach
The rapid proliferation of complex information systems has been met by an ever-increasing quantity of exploits that can cause …
Benjamin M. Ampel
,
Sagar Samtani
,
Hongyi Zhu
,
Hsinchun Chen
Last updated on Feb 5, 2026
PDF
DOI
Improving Threat Mitigation Through a Cybersecurity Risk Management Framework: A Computational Design Science Approach
Cyberattacks have been increasing in volume and intensity, necessitating proactive measures. Cybersecurity risk management frameworks …
Benjamin M. Ampel
,
Sagar Samtani
,
Hongyi Zhu
,
Hsinchun Chen
Last updated on Feb 5, 2026
PDF
DOI
Why Following Friends Can Hurt You: A Replication Study
This study is a methodological replication of the work originally published in Information Systems Research by Krasnova et al. (2015). …
Benjamin M. Ampel
,
Steven Ullman
Last updated on Feb 5, 2026
PDF
DOI
Evading Anti-Phishing Models: A Field Note Documenting an Experience in the Machine Learning Security Evasion Competition 2022
Although machine learning-based anti-phishing detectors have provided promising results in phishing website detection, they remain …
Yang Gao
,
Benjamin M. Ampel
,
Sagar Samtani
Last updated on Feb 5, 2026
PDF
DOI