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. For doing this, please discuss the lab’s system admin (Eunsoo Kim); you should create your own accounts to use seclab server and WordPress, respectively (probably, you can find many useful documents and templates from our file server — “”).
  4. Install a LaTeX distribution on your machine (in order to actually compile LaTeX documents, you also need to install an editor. For windows, the most used editors are probably Texmaker and TeXnicCenter). LaTeX is the de-facto standard for the communication and publication of scientific documents (see LaTeX resources and examples).
  5. 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).
  6. Please provide your regular weekly timetable to Prof. Hyoungshick Kim  via email. It will be helpful to reschedule the lab events.
  7. 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.
  8. If you don’t have a personal web page, then create it. Otherwise, update it with your new status, contact information, and affiliation. Create a link from your record in the People page to your home page.
  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