Reference no: EM132349128
Project: "Detection of phishing websites using machine learning framework"
Project background, goals and Objectives:
Today, phishing, is one of the most common social engineering attack type used by cyber attackers to lure unsuspecting online users to disclose their sensitive information like passwords, personal identification numbers (PINs), etc.
There are many phishing detection systems have been proposed to combat the increasing number of phishing threats, such as blacklist or whitelist, heuristic and visual similarity-based methods proposed to date, but online users are still getting trapped into revealing sensitive information in phishing websites.
The primary objective of this project is to provide a machine learning framework for Detection of phishing websites.
1. Project Resources :
Programming in R (can use Rstudio), machine leaning algorithms
2. Desired Outcomes/Deliverables
• Understand social engineering attack types
• Literature survey on the topic
• Primary objective of this project is to provide a machine learning framework for Detection of phishing websites.
• Research papers
Its a final semester project having 4000 to 5000 words proper professional report using machine learning algorithms/framework to find out the detection of phishing and develop a new idea on the basis of literature reviews and previous research works. So its a totally software base project in which we have to develop a kind of software by coding. So its not just a literature review but we have to develop a new system to detect phishing on the basis of previous researches and literature reviews and have to show the implementation of developed system that how will it work.
And include all the tools, machine learning algorithms/frameworks and implementations.
Structure of project report should be appropriate including:
1) Abstract,
2) table of content,
3) introduction,
4) problem statement,
5) proposed system,
6) literature review,
7) design and architecture,
8) implementation,
9) tools used and software used, 10) experiments and result, and
11) conclusion and
12) finally IEEE style references.
Attachment:- Detection of phishing websites.rar