The effects of social influence and homophily suggest that both network structure and node-attribute information should inform the tasks of link prediction and node-attribute inference. Recently, Yin et al. [2010a, 2010b] proposed an attribute-augmented social network model, which we call Social-Attribute Network (SAN), to integrate network structure and node attributes to perform both link prediction and attribute inference. They focused on generalizing the random walk with a restart algorithm to the SAN framework and showed improved performance. In this article, we extend the SAN framework with several leading supervised and unsupervised link-prediction algorithms and demonstrate performance improvement for each algorithm on both link prediction and attribute inference. Moreover, we make the novel observation that attribute inference can help inform link prediction, that is, link-prediction accuracy is further improved by first inferring missing attributes. We comprehensively evaluate these algorithms and compare them with other existing algorithms using a novel, large-scale Google+ dataset, which we make publicly available (http://www.cs.berkeley.edu/~stevgong/gplus.html).

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We propose a novel approach to infer protocol state machines in the realistic high-latency network setting, and apply it to the analysis of botnet Command and Control (C&C) protocols. Our proposed techniques enable an order of magnitude reduction in the number of queries and time needed to learn a botnet C&C protocol compared to classic algorithms (from days to hours for inferring the MegaD C&C protocol). We also show that the computed protocol state machines enable formal analysis for botnet defense, including finding the weakest links in a protocol, uncovering protocol design flaws, inferring the existence of unobservable communication back-channels among botnet servers, and finding deviations of protocol implementations which can be used for fingerprinting. We validate our technique by inferring the protocol state-machine from Postfix's SMTP implementation and comparing the inferred statemachine to the SMTP standard. Further, our experimental results offer new insights into MegaD's C&C, showing our technique can be used as a powerful tool for defense against botnets.

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Background : Although the pattern of cancer incidence in South Korea is not the same as that of western countries, urological cancer will become one of the major cancers in South Korea in the near future. The pattern of cancer in South Korea is becoming steadily similar to that in western countries. It is, therefore, important to understand the epidemiological features of cancer. Surveillance of cancer incidence and mortality trends provides clues to etiology and helps to assess the effects of improved diagnostic, screening and intervention measures. Methods : The subjects of the study were 13 208 patients living in South Korea, newly diagnosed with urological cancer during the period of 1985-1999. The data were analyzed by age, sex, geography and period of diagnosis