NII Internship
We are happy to work with motivated internship students.
However, the acceptance ratio of the NII Internship is getting lower, so
I hope applicants prepare a well-written application form.
Some specific issues:
- Our lab only accepts longer stay (5-6 months).
- We cannot support intern's flight fees.
- Please send kensuke your CV that describes your skills, e.g. English, research papers, github repository.
- An intern topic for Ph.D students could be flexible depending on their own Ph.D topics.
Possible topics (FY2026)
(1) Network security measurement and analysis
The goal of this topic is to understand network characteristics in terms of network security. The area of the work is very broad (e.g., web browser security/privacy, traffic anomaly detection, DNS, IoT, IPv6, bitcoin transactions). Applicants could propose their interests to fix a specific topic. Depending on the topics, Applicants require enough knowledge on programming languages and machine learning algorithms.
related papers:
(2-1) System log analysis
The goal of this topic is to extract useful knowledge on system failures (i.e., pinpointing root causes, predicting further failures) from a large number of system logs (syslog). Applicants should have enough knowledge on python for data processing.
related papers:
(2-2) System configuration analysis with LLMs
The goal of this topic is to explore applications of LLMs (large language models) for network analysis/management (e.g., misconfig detection, config repair, and config synthesis). Applicants should have enough knowledge on netwrok configs (e.g., Linux, Cisco, Juniper) and LLMs.
(3) Network visualization
The goal of this topic is to propose a fancy method for visualizing IPv6 address assignments in ISPs. This kind of visualization helps researchers in better understaning ISP's address usages (home, mobile, cloud, servers). Applicants should have enough knowledge on python or javascript for visualization.
(4) Web security/privacy
The goal of this topic is to characterize security/privacy risks in web browsers and their extentions. This characterization is important for developing countermeasure. Applicants should have enough knowledge on javascript and/or python.
related papers:
Contact
kensuke (at mark) fukuda-lab (dot) org