our chosen project subject is ” FRAUD DETECTION SYSTEM USING
MACHINE LEARNING “
write a brief proposal (at most one-page, 12-point font, single spacing, 1 inch margins) that describes the idea for a project, the work you intend to perform, and all the people involved in the project (4 people). In particular, it should identify the project type, the problem you plan to address, the motivation for why you find the problem important or interesting, any previous work you already know about, and a rough tentative approach to solving the problem (if applicable) .
In the group project, each group (three to four students) will focus on a topic and comes with a research/technical paper by the end of the semester. The topic should be on any specific security topic, but the expectation is to define a specific problem for in-depth investigation, coming up with a new solution (conceptual or practical application) and compare with similar other approaches extensively.
Your research project paper must include at least 15 articles from IEEE or ACM digital library and should follow IEEE format.
A good resource to search for journal and conference papers: https://scholar.google.com/
There are various types of projects you can consider:
- The project may be very practical in terms of applying techniques you have learned in the course to a real problem such as classification of email messages
- The project may involve designing or adapting existing algorithms to a novel class of problems. For example, how might we solve multiple related classification tasks? How can we improve document clustering by designing a new clustering metric?
- The project may consist of a theoretical analysis of a method we have discussed. For example, this may be in terms of complexity, convergence, etc.
- The project can be a theoretical or more applied survey of a branch of machine learning that we didn’t go through in detail. For example, you may write about the use of machine learning in different domains.
The requirement of the research project is to conduct machine learning techniques using a Weka package or other available programs. You can use any packages or any programming language.
Data can be collected from public domains or from your company.