Research Article
PJC: A Multi-source Method for Identifying Information Dissemination in Networks
@INPROCEEDINGS{10.1007/978-3-030-21373-2_20, author={Yong Ding and Xiaoqing Cui and Huiyong Wang and Yujue Wang}, title={PJC: A Multi-source Method for Identifying Information Dissemination in Networks}, proceedings={Security and Privacy in New Computing Environments. Second EAI International Conference, SPNCE 2019, Tianjin, China, April 13--14, 2019, Proceedings}, proceedings_a={SPNCE}, year={2019}, month={6}, keywords={Information dissemination PJC Identification of multi-source}, doi={10.1007/978-3-030-21373-2_20} }- Yong Ding
Xiaoqing Cui
Huiyong Wang
Yujue Wang
Year: 2019
PJC: A Multi-source Method for Identifying Information Dissemination in Networks
SPNCE
Springer
DOI: 10.1007/978-3-030-21373-2_20
Abstract
With the development of science and technology, the world has become increasingly closely linked. While enjoying the convenience brought by the Internet, we are also facing the danger of risk dissemination. This problem has become more challenging in real-world networks. In this paper, in view of the outbreak of network threats, such as malware, computer viruses, rumors, etc. It is particularly important to identify the source of network threats. In this paper, we have done the following work. Firstly, we draw on the propagation models from epidemiology and design an algorithm partitioned Jordan Center (PJC) to locate the multiple propagation sources. Then, by establishing an extended model originated from propagation sources, we derive the number of sources of estimation. In order to evaluate the performance of the proposed method, a series of experiments were carried out in real-world network topologies. Experimental results show that the method is more accurate than the existing methods.
