Data drives digital border security
Outstanding immigration officers fuel advances in keeping checkpoints secure
Port intelligence explorer
Lin Cong, 43, an immigration police officer with 20 years of service at Huanggang border checkpoint in Shenzhen, Guangdong, is another big data trailblazer.
Joining the Shenzhen general station of exit and entry border inspection after university, he has turned routine passenger inspections into a master class in observation. Using gaps between duties, he studied document verification and compiled key points, counterfeit traits and personnel characteristics in his notebook — mastering passports and entry-exit patterns from hundreds of countries.
Lin has delved into big data intelligence analysis since joining the force in July 2005. In March 2015, he participated in the investigation of a 430-million-yuan case, working round-the-clock for seven days to uncover a gang of over 100 suspects fraudulently obtaining exit-entry documents.
After successfully solving this major case, Lin did not stop his pursuit. Over the next year, he used big data to assist in arresting dozens of fugitives and recovering over 1 billion yuan in economic losses — further fueling his passion for big data analysis.
Huanggang Port in southern Shenzhen is Asia's largest 24-hour land port and has inspected nearly 1 billion passengers and 200 million vehicles since its establishment in 1988. As China's economy and international exchanges thrive, border security challenges have grown rapidly.
Lin addresses this by immersing himself in inspection sites, analyzing data patterns to boost efficiency and crackdown intensity. Using his expertise, Lin built a land port risk screening and early warning system integrating multi-port data screening, tactical application and platform matching. This marked the "first step" in systematic big data screening for China's immigration management, exposing illegal entry tactics.
Starting from the end of 2017, Lin and his team have conducted retrospective analysis of thousands of past cases one by one, summarizing patterns and conducting repeated verifications. This has enabled the proactive pre-positioning of high-risk individuals matching model parameters to on-site inspection personnel, driving a leapfrog transformation in border checkpoint enforcement models — from "waiting passively for suspects" to "taking proactive action".
"We've broken data barriers, formed joint forces and brought modeling into the digital era," Lin said.
"It's nothing if I alone set a good example. I need to let my colleagues across the national immigration management system know that big data is effective and easy to use. Big data empowering immigration management has become an inevitable trend of the times."
For his outstanding contributions, Lin has been awarded one First-Class Individual Merit, one Second-Class Individual Merit and four Third-Class Individual Merits. He was named a "Model Individual" in the Ministry of Public Security's national police training campaign and conferred the title of "Second-Class Model Hero of the National Public Security System" in June 2021.
The NIA said that in the coming years it will strengthen the digital intelligence, equipment, system and organizational advantages of immigration governance, and further improve the system for fostering new-quality combat capabilities.
yangzekun@chinadaily.com.cn
