Mahima Chowdary Mannava

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About

Mahima Chowdary Mannava is a researcher at the forefront of cybersecurity and artificial intelligence, with a primary focus on adversarial machine learning and captcha security. Her most-cited work, "CNN Combined with FC Classifier to Combat Artificial Penta-Digit Text-Based Captcha" (2023), has garnered 7 citations, establishing her as an emerging voice in the battle against automated captcha-breaking systems. In this study, Mannava pioneered a hybrid deep learning architecture that integrates convolutional neural networks with fully connected classifiers, achieving remarkable accuracy in deciphering distorted text-based captchas—a critical contribution to understanding and strengthening web security mechanisms. Her work directly addresses the arms race between captcha designers and AI-based attackers, offering both a proof-of-concept for vulnerability assessment and a foundation for developing more resilient authentication systems. Beyond this flagship paper, Mannava’s research explores the broader implications of neural network robustness, making her insights valuable for students and practitioners working at the intersection of computer vision and cybersecurity. Her concise yet impactful publication record signals a promising trajectory in applied deep learning research.