Research indicates that deceitful videos tend to spread rapidly online and influence people's opinions and ideas. Because of this, video misinformation via deepfake video manipulation poses a significant online threat. This study aims to discover what factors can influence viewers' capability to distinguish deepfake videos from genuine video…

Misinformation and Disinformation, both types of Information Disorder in the cyber world, operate on a systemic level. Several factors enabling their persistence, including laws, policies, and technological mediators, have been investigated in the literature. Cybersecurity frameworks and guidelines specify that the target victims, as part of the…

Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…

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…

Defenses against adversarial attacks are essential to ensure the reliability of machine learning models as their applications are expanding in different domains. Existing ML defense techniques have several limitations in practical use. I proposed a trustworthy framework that employs an adaptive strategy to inspect both inputs and decisions. In…

"Biometrics" are physical or behavioral human characteristics that can be used to identify a person. It is widely known that keystroke or typing dynamics for short, fixed texts (e.g., passwords) could serve as a behavioral biometric. In this study, we investigate whether keystroke data from essay responses can lead to a reliable…

The number of malicious files present in the public domain continues to rise at a substantial rate. Current anti-malware software utilizes a signature-based method to detect the presence of malicious software. Generating these pattern signatures is time consuming due to malicious code complexity and the need for expert analysis, however, by making…

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…

The majority of documented phishing attacks have been carried by email, yet few studies have measured the impact of email headers on the predictive accuracy of machine learning techniques in detecting email phishing attacks. Research has shown that the inclusion of a limited subset of email headers as features in training machine learning…

With increasing Internet connectivity and traffic volume, recent intrusion incidents have reemphasized the importance of network intrusion detection systems for combating increasingly sophisticated network attacks. Techniques such as pattern recognition and the data mining of network events are often used by intrusion detection systems to classify…

Multi-touch tablets allow users to interact with computers through intuitive, natural gestures and direct manipulation of digital objects. One advantage of these devices is that they can offer a large, collaborative space where several users can work on a task at the same time. However the lack of privacy in these situations makes standard…