Starting at seclab

seclab welcomes its new members!

To facilitate your successful settlement in the SKKU ECE and seclab, you are encouraged to take the following steps in the specified order:

  1. Set up your desk in the office #27317, Eng. 2. You need to get the 4-digit secret code from a lab member to access to the office.
  2. Set up your computer. To install some necessary software (e.g. Windows OS), you can borrow DVDs from the office #27421, Eng. 2.
  3. Set up your network environments. To do this, please discuss with the lab’s system admin (Eunsoo Kim).
  4. If you don’t have a SKKU account, then create it at Please use your English name rather than nickname for your official SKKU account if you can (it would be helpful for you if you want to pursue a career in the academy).
  5. Please provide your regular weekly timetable to Prof. Hyoungshick Kim  via email. It will be helpful to reschedule the lab events.
  6. If you don’t have Google and Dropbox accounts, then create them. We use Google Calendar which should make scheduling events easier and Dropbox which should make file sharing easier. Provide your account information to Prof. Hyoungshick Kim via email.
  7. Contact the lab’s system admin with a photo of yourself, your new status, contact information, and affilication. The admin will update your web page at People using the information you provide.
  8. Visit Overleaf and sign up using either your email address or Google account. Overleaf is a collaborative cloud-based LaTeX editor used for writing, editing and publishing scientific documents. You will be using it a lot when writing your own research paper or when co-authoring with your colleagues and/or other researchers. If you are in need for creating a new project through Overleaf, contact the admin with the project name and your Overleaf account.
  9. Please check the minimum requirements for Seclab students.


Problem Solving


Writing reviews



How to research

Academic services

Statistical methods

Security courses

Computer Science courses

Machine Learning courses




Programming Language

Offensive Security Tools

Machine Learning

Security paper