Project Name: Machine Learning Based Encrypted Network Traffic Analysis on Multicore Processors
Principal Investigator, Faculty Mentor: Dr. Peilong Li
Student Researchers: Derek Manning
Grant Amount: $6,200
Project Duration: 10 Weeks
Abstract Applying machine learning techniques to detect malicious encrypted network traffic has become a challenging research topic since traditional approaches based on studying network patterns fail to operate on encrypted data, especially without compromising the integrity of encryption. Traditional solutions to identify network threats fall into two major categories: 1) deep packet inspection and signatures; and 2) offline network pattern training.