Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Comparative Study of Machine Learning Algorithms for Fraud Detection in Blockchain(Institute of Electrical and Electronics Engineers Inc., 2021) Bhowmik, M.; Sai Siri Chandana, T.; Rudra, B.Fraudulent transactions have a huge impact on the economy and trust of a blockchain network. Consensus algorithms like proof of work or proof of stake can verify the validity of the transaction but not the nature of the users involved in the transactions or those who verify the transactions. This makes a blockchain network still vulnerable to fraudulent activities. One of the ways to eliminate fraud is by using machine learning techniques. Machine learning can be of supervised or unsupervised nature. In this paper, we use various supervised machine learning techniques to check for fraudulent and legitimate transactions. We also provide an extensive comparative study of various supervised machine learning techniques like decision trees, Naive Bayes, logistic regression, multilayer perceptron, and so on for the above task. © 2021 IEEE.Item Optimized Lattice-Based Homomorphic Encryption for Secure Multiparty Computation in Group Communication(Institute of Electrical and Electronics Engineers Inc., 2024) Renisha, P.S.; Rudra, B.This research work describes a framework for secured and effective way of group interaction incorporating classical cryptography and quantum communication technique. This framework employs a classical cryptographic methods for group logistics like as transmitting of messages and membership management while employing quantum communication strategy for secure key distribution and related authentication. In order to increase the flexibility and datasecurity of the proposed system further, a supervisor learning based mechanism is incorporated into the framework where reinforcement learning will employed in controlling the interaction of the protocols and the decision-making processes in an active manner. This combination of classical, quantum and supervisor learning strategies gives a solution to the issues of scalability, efficiency, effective and timely actionable response to increasing cyber threats especially in the era of quantum computing. The framework is highly effective and secured for group interaction in distributed network infrastructures. It will be a leading the approach for advanced cryptographic mechanism in the future. © 2024 IEEE.Item A Hybrid Framework for Secure Group Communication Using Quantum-Classical Cryptography and Reinforcement Learning(Institute of Electrical and Electronics Engineers Inc., 2025) Renisha, P.S.; Rudra, B.This research work describes a framework for secured and effective way of group interaction incorporating classical cryptography and quantum communication technique. This framework employs a classical cryptographic methods for group logistics like as transmitting of messages and membership management while employing quantum communication strategy for secure key distribution and related authentication. In order to increase the flexibility and data-security of the proposed system further, a supervisor learning based mechanism is incorporated into the framework where reinforcement learning will employed in controlling the interaction of the protocols and the decision-making processes in an active manner. This combination of classical, quantum and supervisor learning strategies gives a solution to the issues of scalability, efficiency, effective and timely actionable response to increasing cyber threats especially in the era of quantum computing. The framework is highly effective and secured for group interaction in distributed network infrastructures. It will be a leading the approach for advanced cryptographic mechanism in the future. © 2025 IEEE.