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Fake base station (FBS) has been exploited by criminals to attack mobile users by spamming fraudulent messages for over a decade. Despite that prior work has proposed several techniques to mitigate this issue, FBS spam is still a long-standing challenging issue in some countries, such as China, and causes billions of dollars of financial loss every year. Therefore, understanding and exploring the thematic strategies in the FBS spam ecosystem at a large scale would improve the defense mechanisms. In this paper, we present the first large-scale characterization of FBS spam ecosystem by collecting three-month real-world FBS detection results. First, at "macro-level'', we uncover the characteristics of FBS spammers, including their business categories, temporal patterns and spatial patterns. Second, at "micro-level'', we investigate how FBS ecosystem is organized and how fraudulent messages are constructed by campaigns to trap users and evade detection. Collectively, the results expand our understanding of the FBS spam ecosystem and provide new insights into improved mitigation mechanisms for the security community.

The contents of modern medicine are various and complicated, so clinicians need to master more about medical knowledge. This paper introduces a medical process visualization clinical medical decision support system (CDSS) oriented to NCCN clinical practice guidelines, which can assist clinicians to make diagnosis and treatment decisions. And a new knowledge representation model is designed for NCCN guidelines. The model can express medical knowledge freely and flexibly, and medical knowledge also can be updated in time. At present, medical process visualization CDSS has been implemented for many different cancers.

The popularity of online gambling could bring negative social impact, and many countries ban or restrict online gambling. Taking China for example, online gambling violates Chinese laws and hence is illegal. However, illegal online gambling websites are still thriving despite strict restrictions, since they are able to make tremendous illicit profits by trapping and cheating online players. In this paper, we conduct the first deep analysis on illegal online gambling targeting Chinese to unveil its profit chain. After successfully identifying more than 967,954 suspicious illegal gambling websites, we inspect these illegal gambling websites from five aspects, including webpage structure similarity, SEO (Search Engine Optimization) methods, the abuse of Internet infrastructure, third-party online payment, and gambling group. Then we conduct a measurement study on the profit chain of illegal online gambling, investigating the upstream and downstream of these illegal gambling websites. We mainly focus on promotion strategies, third-party online payment, the abuse of third-party live chat services, and network infrastructures. Our findings shed the light on the ecosystem of online gambling and help the security community thwart illegal online gambling.