The research project is proposed as a novel approach for detecting encrypted malicious TLS network traffic by using Quantum Deep Learning. Without decrypting the traffic, by using the metadata (packet-level) information alone, the model can do the detection. The project involved multiclassification on TLS-based encrypted attacks and binary classification over TLS-based malicious network traffic by using Quantum Computing and Quantum Deep Learning.
Security and cryptocurrency wallet use are still at the center of the issues with blockchain adoption. Seed phrase-based physical wallets…
The existing traditional e-commerce systems struggle to focus the user query to give a relevant product recommendation at the end…
“The wristGuard application employs a hybrid approach, combining deep learning models for feature extraction and stacking ensemble method for classification…
“The COVID-19 epidemic changed IT industry processes by hastening the introduction of remote work. In virtual workplaces, detecting employee engagement…
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