Hema Pavithra Sundaramoorthy

Title of my thesis: Classification of Internet Traffic via TLS1.3 using Deep Learning Extracting the different statistical features from the Internet traffic generated by various applications (e.g. Snapchat, Tiktok, etc) and classifying them using deep learning models (like MLP, CNN). Tools: Python, Wireshark, MS Excel, Git, Docker

Title of my project: Network Traffic Classification with Machine Learning Adopting various machine learning algorithms (like KNN, Decision Tree, Naive Bayes) to classify the encrypted packets based on the applications (e.g. Skype, Hangout, etc) which are responsible for generating the traffic. Tools: MATLAB, Weka, Wireshark, MS Excel

Extracting the data from websites (European electricity powerplant details), analyzing them and visualizing it. Tools: Python, SQL, Git, MS Excel

Analysis of the impact of WP.29 on the automotive industry, as well as the cybersecurity of vehicles. Possible preparations of automotive manufacturers for future standards • Modelling cooperation between automotive manufacturers and suppliers to meet future requirements • Integration of WP.29 requirements into the product life cycle • Establishment of a cyber security strategy for automotive manufacturers that are compliant with WP.29 requirements

Management of trading related application and analysis of its impact. Data analysis and visualizing (with database related to trading and logistics). Tools: Qlik, SQL, DataStage, MS Excel

Machine Learning (Research Project), Deep Learning (Master's thesis), Digital Communication, 3D Computer Vision, Digital Audio Signal Processing, Digital Image Analysis, Pattern Recognition, Information Theory and Coding

Signals & Systems, Digital Signal Processing, Communication Theory, Computer Networks, Digital Image Processing