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Xuandong Zhao – ProQuest LLC, 2024
The rapid advancement of powerful Large Language Models (LLMs), such as ChatGPT and Llama, has revolutionized the world by bringing new creative possibilities and enhancing productivity. However, these advancements also pose significant challenges and risks, including the potential for misuse in the form of fake news, academic dishonesty,…
Descriptors: Computational Linguistics, Intellectual Property, Artificial Intelligence, Productivity
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Aruta, John A.; Schembari, N. Paul – Journal of Cybersecurity Education, Research and Practice, 2020
We describe the results of a master's thesis in malware detection and discuss the connection to the learning goals of the project. As part of the thesis, we studied obfuscation of malware, conversion of files into images, image processing, and machine learning, a process of benefit to both the student and faculty. Malware detection becomes…
Descriptors: Computer Software, Computer Security, Identification, Deception
Mbaziira, Alex Vincent – ProQuest LLC, 2017
Cybercriminals are increasingly using Internet-based text messaging applications to exploit their victims. Incidents of deceptive cybercrime in text-based communication are increasing and include fraud, scams, as well as favorable and unfavorable fake reviews. In this work, we use a text-based deception detection approach to train models for…
Descriptors: Crime, Information Security, Models, Networks
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Cannizzaro, Michael; Reilly, Nicole; Snyder, Peter J. – Journal of Psycholinguistic Research, 2004
The present study investigated the utility of employing computerized speech content analysis software to detect feigned depression in psychologically healthy adults. Twenty-two subjects between the ages of 19 and 54 years old, who scored lower than 10 on the Beck depression inventory (BDI, 1996), were asked to speak freely in response to a neutral…
Descriptors: Speech, Content Analysis, Depression (Psychology), Deception