Poster 1: Machine Learning for Network Intrusion Detection
During our 8-week SVCSI Summer Camp 2021, We had a great opportunity to tutor many high school and undergraduate students. Guiding them has been an exceptional experience for all of us, and we are proud to present the fruits of our students’ efforts: a total of seven research projects in different areas of the cybersecurity domain.
In the first poster, Dr. Younghee Park tutored her students on a research project called “Machine Learning for Network Intrusion Detection”. In this work, the students had to pre-process the network data, apply machine learning algorithms, and detect malicious traffic due to malware intrusion. In the second poster, Dr. Nima Karimian proposed “ECG Biometrics”. In this project, his students were introduced to Biometrics and, more specifically, ECG features to track the rate and pattern of a person’s heartbeat. Poster number three is “Phishing URL Detection”, where Dr. Jorjeta Jetcheva educated the students about the risks of phishing through malicious URLs. Here, students embedded an AI-powered phishing URL detector in state-of-the-art chatbots to avoid the spread of malicious URLs. “Evaluating Mining Pools in SpartanGold” is the title of the fourth research project. Dr. Thomas H. Austin introduces the students to blockchain technology by conducting a “pool-hopping” attack against the educational-based blockchain “SpartanGold”. In the fifth project, Dr. Fabio Di Troia guided his students on “Advanced Malware Detection via Machine Learning”. In this work, the students familiarized themselves with the detection of highly obfuscated malware samples through the application of machine learning algorithms. Dr. Sang-Yoon Chang proposed “Build Your Own Cryptocurrency” to his students, which had the opportunity to build a totally functional and charity-supporting cryptocurrency named SVCFC. Last but not least, Dr. Gokay Saldamli and his students worked on “AES Cipher”, where they faced the challenging problem of reducing the execution time of the well-known AES cipher by proposing a parallel implementation of such algorithm.