Abstract: The increasing adoption of online education has led to a growing need for secure and reliable examination systems. Traditional in-person examinations ensure integrity through physical invigilation, but with the rise of remote learning, maintaining exam security has become a significant challenge. Online exams are often vulnerable to cheating, impersonation, and unauthorized assistance, which undermines the credibility of assessments.
Existing online examination systems employ manual proctor- ing, where human invigilators monitor students via webcams. However, this approach is labor-intensive, expensive, and sub- ject to human errors. To address these challenges, automated proctoring solutions have been introduced, integrating artificial intelligence (AI) and machine learning to detect suspicious behavior.
In this research, we present Proctor, an AI-based online proctoring system designed to ensure exam integrity through automated monitoring and real-time analysis. The system uses computer vision techniques to detect face absence, multiple peo- ple in the frame, mobile phone usage, and unauthorized objects. Additionally, it prevents tab switching, keyboard shortcuts, and right-click actions, further securing the examination process.
Proctor is designed to be efficient, scalable, and user-friendly, making online assessments more reliable without requiring hu- man invigilators. By leveraging advanced AI models, the system enhances security while reducing the administrative burden on educators. This research explores the need, implementation, and effectiveness of AI-based proctoring, offering a novel approach to securing online exams.
|
DOI:
10.17148/IJARCCE.2025.14544
