This study examines technological strategies implemented to prevent examination malpractices in higher education, focusing on secure platforms, biometric authentication, online proctoring, and adaptive assessment designs. Employing a hybrid research framework, it integrates quantitative surveys, qualitative interviews, pilot program observations, and platform analytics to evaluate efficacy and user experience across diverse academic disciplines. Findings indicate that multi-layered security configurations combining biometric verification, AI-assisted proctoring, randomized question delivery, and blockchain-based audit trails reduce misconduct incidence while maintaining fairness and user acceptance. The research highlights the importance of balancing automated detection with human oversight, ensuring infrastructural readiness, and providing transparent communication to address privacy and usability concerns. Results also reveal discipline-specific variations in adoption and effectiveness, with STEM fields showing greater gains linked to interactive assessment formats. The integration of generative AI tools presents both opportunities for enhanced feedback and challenges related to potential exploitation, underscoring the need for careful design and monitoring. Hence, the outcomes suggest that thoughtfully implemented technological interventions can support academic integrity by aligning security measures with pedagogical objectives and stakeholder engagement.