A botnet is a collection of bots, each generally running on a compromised system and responding to commands over a "command-andcontrol" overlay network. We investigate observable differences in the behavior of bots and benign programs, focusing on the way that bots respond to data received over the network. Our experimental platform monitors program behavior, considering data received over the ...

We develop a technique to identify abnormally correlated user accounts in Twitter, which are very unlikely to be human operated. This new approach of bot detection considers cross-correlating user activities and requires no labeled data, as opposed to existing bot detection techniques that consider users independently, and require large amount of recently labeled data. Our system uses a lag-sen...

A botnet is a collection of bots, each generally running on a compromised system and responding to commands over a “commandand-control” overlay network. We investigate observable differences in the behavior of bots and benign programs, focusing on the way that bots respond to data received over the network. Our experimental platform monitors execution of an arbitrary Win32 binary, considering d...

Some fear that social bots, automated accounts on online networks, propagate falsehoods can harm public opinion formation and democratic decision-making. Empirical research, however, resulted in puzzling findings. On the one hand, content emitted by bots tends to spread very quickly networks. other it turned out bots’ ability contact human users be limited. Here we analyze an agent-based model ...

Bots are the root cause of many security problems on the Internet – they send spam, steal information from infected machines, and perform distributed denial of service attacks. Given their security impact, it is not surprising that a large number of techniques have been proposed that aim to detect and mitigate bots, both network-based and host-based approaches. Detecting bots at the network-lev...

BACKGROUND As e-cigarette use rapidly increases in popularity, data from online social systems (Twitter, Instagram, Google Web Search) can be used to capture and describe the social and environmental context in which individuals use, perceive, and are marketed this tobacco product. Social media data may serve as a massive focus group where people organically discuss e-cigarettes unprimed by a r...

AIM The aim of the present study was to evaluate the characteristics of borderline ovarian tumors (BOTs). PATIENTS AND METHODS Data of 151 patients with BOTs were retrospectively evaluated. RESULTS A total of 151 cases with BOTs were diagnosed. Histopathological evaluation identified 82.8% with serous, 10.6% with mucinous and 5.3% with mixed histology. Overall, 67.5% had International Feder...