Secure Online Recruitment System (JobSafe)

Eng, Zhi Xuan (2026) Secure Online Recruitment System (JobSafe). Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

Text RIS_Eng Zhi Xuan_Fulltext.pdf Restricted to Registered users only Download (10MB)

Abstract

The proposed project Secure Online Recruitment System (JobSafe) aims to address the problem of traditional job portals such as resume leaks, personal data privacy concerns, fake job listings and ineffective job matching. These problems are vulnerable to scams and the misuse of their personal information. The objective of this project is to create a secure platform to safeguard resume files using AES encryption, verify employer account through admin-reviewed documentation and improves job matching accuracy with AI-powered filtering deep learning semantic matching techniques. The scope of the proposed system includes user authentication and login module, resume management, AI-powered job matching, job application, employer account verification, job posting management and advertisement package management. The system features are tailored for different user roles such as job seekers, employers and administrators. The proposed system is developed using the Incremental Development Model to allow the system scope to be broken into smaller and manageable parts. C# ASP.NET MVC is used for backend development and Entity Framework Core is implemented for database interaction. In addition, Sentence-BERT with cosine similarity is adopted to match applicants to relevant job postings based on their resume content. Moreover, fact gathering techniques such as questionnaires and documentation review were conducted to collect user requirements and guide the design of system features. System testing involved functional testing of modules, usability feedback from simulated users and evaluation of encryption and AI model accuracy. The results show that the proposed system successfully meets the goals in protecting resume files, preventing unauthorized employer access and improved job recommendations relevance. Although the system provides good security and smart features, some areas can still be improved. These include making the employer screening process more automated and improving the accuracy of the AI job matching. Overall, the project meets its main purpose and offers a secure, smart and easy-to-use recruitment platform.