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      Detecting Web-Based Botnets Using Bot Communication Traffic Features

      , , , ,
      Security and Communication Networks
      Hindawi Limited

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          Abstract

          Web-based botnets are popular nowadays. A Web-based botnet is a botnet whose C&C server and bots use HTTP protocol, the most universal and supported network protocol, to communicate with each other. Because the botnet communication can be hidden easily by attackers behind the relatively massive HTTP traffic, administrators of network equipment, such as routers and switches, cannot block such suspicious traffic directly regardless of costs. Based on the clients constituent of a Web server and characteristics of HTTP responses sent to clients from the server, this paper proposes a traffic inspection solution, called Web-based Botnet Detector (WBD). WBD is able to detect suspicious C&C (Command-and-Control) servers of HTTP botnets regardless of whether the botnet commands are encrypted or hidden in normal Web pages. More than 500 GB real network traces collected from 11 backbone routers are used to evaluate our method. Experimental results show that the false positive rate of WBD is 0.42%.

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          Most cited references11

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          The Rise of Social Bots

          , , (2015)
          The Turing test aimed to recognize the behavior of a human from that of a computer algorithm. Such challenge is more relevant than ever in today's social media context, where limited attention and technology constrain the expressive power of humans, while incentives abound to develop software agents mimicking humans. These social bots interact, often unnoticed, with real people in social media ecosystems, but their abundance is uncertain. While many bots are benign, one can design harmful bots with the goals of persuading, smearing, or deceiving. Here we discuss the characteristics of modern, sophisticated social bots, and how their presence can endanger online ecosystems and our society. We then review current efforts to detect social bots on Twitter. Features related to content, network, sentiment, and temporal patterns of activity are imitated by bots but at the same time can help discriminate synthetic behaviors from human ones, yielding signatures of engineered social tampering.
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            Botnets and Internet of Things Security

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              Botnet detection based on traffic behavior analysis and flow intervals

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                Author and article information

                Journal
                Security and Communication Networks
                Security and Communication Networks
                Hindawi Limited
                1939-0114
                1939-0122
                2017
                2017
                : 2017
                :
                : 1-11
                Article
                10.1155/2017/5960307
                3abed0df-4018-46e0-b610-aeb053db4a2f
                © 2017

                http://creativecommons.org/licenses/by/4.0/

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