Due to the nature of drug criminal organizations, some of the often hidden behind the leader in a special position to avoid being caught, so when we hit some criminals in the network, these important leaders still can reorganize a new person to replace is arrests for crimes. Therefore, drug crime networks have a great network rebound or anti combat sexual, drug-related crime network is a network with a certain flexibility, while the emergence of drug-related criminal organizations often play but from the phenomenon. The key to keeping drug crime network network resilience lies an important role in the retention of basic crime. Because each character is destroyed after the offender may also be employed instead of by others, only to minimize criminal networks engaged in the important role of crime, and to maximize the potential pressure on the perpetrators of the various roles engaged in criminal activity range, in order to minimize drug-related crimes. This problem is for the article from the perspective of network connectivity (i.e.,"is equivalent to the importance of the node (set) on the network is deleted destructive" by deleting a node (set), the use of the network connectivity of other indicators Changes to determine their importance) for drug offenses network analysis. Extracted from criminal drug cases as a node and the relationship between the type of criminals extracted as the drugs have side to build criminal networks, connectivity is proposed based on the drug-crime networks are the core members of the network mining algorithm for drug offenses excavation, digging out drug crime network in the central figure, including those important people can increase network resiliency or behind the leaders and those who control the spread of information throughout the network of people, and ultimately to achieve the maximum reduction in drug-related crime network network flexibility. And with a visual approach to the analysis results show an intuitive graphical way out, which can be valuable information for drug core members of criminal networks, organizational structure, operations and other laws for better understanding and grasp. Finally, experiments show that the proposed algorithm with high accuracy the core members of the excavation at the center of analysis based on the traditional method, the algorithm described in this paper is effective. |