Date: 28th April 2026
Time: 3:30 PM – 4:30 PM
Venue: Room 303 , SICSR
Mode: Offline
Event Coordinator: Dr. Prakash Raut
Speaker: Dr. Shilpa Sardesai
Dr. Shilpa Sardesai delivered an engaging session on the topic “Secure and Intelligent Financial Data Analysis Using Machine Learning, Fuzzy Logic, and Cryptography.” The session focused on a hybrid framework designed to enhance financial risk analysis by combining advanced machine learning techniques, fuzzy logic, and robust cryptographic mechanisms.
Dr. Sardesai explained how machine learning models such as LSTM and XGBoost can be utilized to accurately predict financial risks and support informed decision-making. She further highlighted the role of fuzzy logic in improving the interpretability of predictions by effectively handling uncertainty and providing reasoning that is easier for humans to understand. To address concerns related to data privacy and security, the framework incorporates cryptographic techniques including AES and RSA encryption, along with federated learning, enabling secure data analysis without exposing sensitive financial information. The session also introduced a fuzzy-based access control system that dynamically regulates user permissions based on trust levels and behavioral patterns. Experimental findings demonstrating high prediction accuracy, enhanced security, and reliable decision-making were discussed, showcasing the framework’s potential applications in areas such as credit scoring, fraud detection, and financial risk management.
Dr. Shilpa Sardesai discussing the integration of machine learning, fuzzy logic, and cryptography for secure financial analytics.
