6Community: An active IPv6 address detection method based on community discovery algorithm

Network management such as topology discovery and network diagnosis needs to be scanned based on the Internet, and the IPV6 address space is huge and it is difficult to perform global scanning. The existing IPV6 target generation method has a low hit rate, mainly because the spatial division of the address is not accurate enough. We propose an IPV6 address prediction method based on community discovery algorithm, which is called 6Community. 6Community first uses the community discovery algorithm to divide the address space, so that similar addresses can be divided into an address area, and then performs anomaly detection on the divided address space, and re-divides the space. Finally, the obtained address patterns are pre-detected to filter out low-quality address patterns and reduce the size of address scanning space, so as to accelerate the speed of address prediction and increase the hit rate of address prediction. We conducted experiments on three data sets. The results show that compared with the existing methods, the IPV6 address hit rate generated by 6Community is improved, which can reach 13.2% -33.5%. At the same time, the results show that the scanning space obtained by this method is reduced, and the abnormal points in the process of experiment are also reduced.