• Mr.M S V V Ramesh
• Mrs.CH. Sri Divya
• Pothumudi Geethika Deepthi
• Patnala Satya Manikanta
• Palepu Veera Venkata Karthik , Dangeti Rupasri

CheatGuardX uses AI technology to establish examination trustworthiness by performing real-time observation and automatic fraud detection functions. Reinforcement Learning-based Convolutional Neural Networks (RL-CNN) enable the system to detect suspicious activities which include improper head movements together with multiple facial appearances and external object usage accurately. This system uses multiple elements including the detection of head pose along with assessment of noise and tracking of objects and faces to secure exam conditions. The warning system operates through a defined protocol which starts with repeated alerts for minor offenses yet triggers instantaneous termination to account for multiple face detection and object regulations. The interface of CheatGuardX allows users to engage easily in assessments but it ensures rigorous monitoring rules along the way. The system efficiently handles video stream processing which leads to reduced latency and improved capability of detecting fraudulent activities. Real-time examination monitoring tools in the Admin Dashboard enable administrators to observe participant status together with violation detection and they can regulate exam permissions while receiving instantaneous reporting data. CheatGuardX demonstrates excellent capacity to scale across large online assessment operations which enables fair and secure remote tests for numerous participants. The evaluation covers system architecture and functionality alongside its effects on remote exam monitoring while proving CheatGuardX as an advanced artificial intelligence solution for testing security.

CheatGuardX, Reinforcement Learning-based Convolutional Neural Networks (RL-CNN), Online Assessment, Artificial Intelligence, Fraudulent Activities.

" CheatGuardX: Redefining Exam Integrity with RL-CNN Intelligence ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.a450-a458, April-2025, Available :http://www.jetir.org/papers/JETIR2504056.pdf

" CheatGuardX: Redefining Exam Integrity with RL-CNN Intelligence ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppa450-a458, April-2025, Available at : http://www.jetir.org/papers/JETIR2504056.pdf