<p>The application of data mining technology in the employment recommendation system for college students is becoming increasingly widespread. However, the complexity of network attack methods and the frequent occurrence of data leakage incidents pose a serious threat to the employment recommendation system for college students. This study aims to explore how to effectively apply data mining technology in the college student employment recommendation system, conducts an in-depth analysis of the application of data mining technology in the college student employment recommendation system, and proposes an intelligent recommendation algorithm based on data mining. In terms of network security, the research has adopted multiple security technologies, including data encryption, access control, intrusion detection, etc., to ensure the integrity, confidentiality and availability of data. The security of the system has been further enhanced by establishing a secure authentication mechanism and an auditing mechanism. The research also tested the performance of the system through experiments, including data processing efficiency, recommendation accuracy and system security. The experimental results show that the proposed intelligent recommendation algorithm can effectively improve the accuracy and efficiency of employment recommendation for college students. In terms of network security, the security of the system has been significantly enhanced by adopting multiple security technologies. Data encryption and access control mechanisms effectively prevent data leakage and unauthorized access, and intrusion detection systems can promptly identify and block potential network attacks. The overall performance of the system has achieved the expected goals in terms of security and recommendation effect. This combination enhances the efficiency and quality of employment recommendations and effectively ensures the security of the system.</p>