International Research Journal of Education and Technology

The rapid growth of professional networking platforms has transformed the way individuals present their professional identity and skills online. Many candidates create digital profiles similar to LinkedIn to showcase their education, experience, and technical abilities. However, the presence of exaggerated or fake skills in such profiles has become a growing concern for recruiters and organisations. This issue can lead to incorrect hiring decisions and reduce the reliability of online professional platforms. Detecting the authenticity of skills listed in user profiles has therefore become an important challenge in modern recruitment systems.

The AI-Based Fake Skill Detection system is developed to analyse and identify potentially misleading or inconsistent skills in LinkedIn-style profiles using artificial intelligence and data analysis techniques. The system gathers information from profile sections such as education, work experience, certifications, projects, and listed skills. By applying machine learning algorithms and natural language processing (NLP), the system evaluates the relationship between the user’s background and the skills mentioned in the profile. This process helps identify patterns that may indicate unrealistic or unsupported skill claims.

The analysed data is processed to generate a credibility assessment of the listed skills. The system produces a report that highlights suspicious skills and provides a skill authenticity score based on the candidate’s qualifications and experience. This allows recruiters and organizations to quickly evaluate profile reliability and make more informed hiring decisions. The proposed system aims to enhance transparency in online professional platforms, support recruiters in identifying genuine candidates, and promote trustworthy digital profiles.

Keywords: Artificial Intelligence, Skill Verification, Fake Skill Detection, LinkedIn