Job seekers face numerous risks like fraudulent job postings and untrustworthy recruiters because computerized systems have changed how job seekers are hired. Recruitments are being done mainly through job portals; however, most job portals still use an outdated verification process (i.e. email/phone) to determine if recruitment sources are legitimate, and provide little protection of legitimacy and safety against returning false applicants. This research looks at a new model referred to as Trust Hire, which is an AI-supported system that validates organizations, by first verifying the personas of recruiters, prior to identifying and mitigating recruiter fraudulent/risk. Components of this E-HRM System (automated document verification, risk assessment, administrative approval) work together to provide greater accountability, safety and efficiency to the computerized (Emodules) hiring system stages.

Describe how the hiring process increases the security and reliability of a module by assigning specific roles to human reviewers for subjective assessments and to automated verification tools for objective checks. The number of tasks during the hiring process is reduced through the integration of automated document verification systems. Combined risk assessment processes and strict administrative approval methods are also applied. This prevents the system from creating duplicate tasks at any phase. As a result, a safer and more trustworthy environment is created for all hiring-related activities. Implementing multiple verification methods, such as automated reference checks and manual performance evaluations, creates a reliable platform and increases assurance for job seekers and employers. A preferred environment should be both visible and flexible for real hiring platforms. This greatly enhances transparency and trust in the hiring process. It also reduces the chance that job seekers will fall prey to sophisticated scams or other fraudulent activity associated with hiring.

I.Al-Jarrah, A., et al. (2018). Trust and Risk in E-Staffing Modules. Journal of Information Security. II.Sharma, R., & Gupta, N. (2020). Analysis of Security Issues in Online Job Portals. International Journal of Computer Applications. III. Singh, P., & Kaur, H. (2019). Challenges in Online Staffing Modules. International Journal of Computer Science Research. IV.Zhang, Y., et al. (2020). Online Job Advertisement Fraud Detection. Springer Lecture Notes in Computer Science. V.J. Smith and L. Brown, “Role-Based Access Control in Web Applications,” IEEE Transactions on Information Forensics and Security, vol. 14, no. 6, pp. 1568–1579, 2019. VI.K. Lee, “Web-Based Systems (Web Systems): Security and Authentication of Databases.” Journal of Information Security, 2011, 11(3), pp. 145 – 152. VII.P. Verma and S. Agarwal, “Fraud Detection in Online Platforms with Machine Learning.” International Journal of Computer Applications, Year: 2019, Volume: 182, Issue: 22, pp. 10 – 15. VIII.T. Nguyen and D. Tran, “Design/Implementing Cloud-Based Recruitment Systems.” International Journal of Cloud Computing, Year: 2020, Volume: 9, Issue: 1, pp. 55 – 63. IX.S. Johnson, “Web Application Architecture (on the Client Side) Using Spring Boot and MySQL.” Journal of Web Engineering Year: 2021, Volume: 19, Issue: 2, pp. 89 – 102 R. Mehta and A. Shah, “Increasing Trust in E-Recruiting via Verification Systems.” International Journal of Engineering Research & Technology, Year: 2019, Volume: 8, Issue: 5, pp. 210 – 215.

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