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This poster deals with botnets, the most dangerous kind of mobile malware, and their detection using neural networks. Unlike common mobile malware, botnets often have a complicated pattern of behavior because they are not managed by predictable algorithms but they are controlled by humans via command and control servers (C&C servers) or via peer-to-peer networks. However, they have certain common...
Mobile devices such as smartphones and tablets have become a common part of human society of the 21st century and their popularity is continuously growing. However, certain research papers imply that popularity and security do not reach the same level. They suggest that there are security weaknesses allowing publishing applications with malicious behavior on Google Play. For test reasons of Google...
Nowadays mobile devices such as smartphones had widely been used. People use smartphones not limited for phone calling or sending messages but also for web browsing, social networking and online banking transaction. To certain extend, all confidential information are kept in their smartphone. As a result, smartphones became as one of the cyber-criminal main target especially through an installation...
Given the popularity of both smartphones and online social networking, it is only a matter of time before attackers exploit both to launch new types of attacks. In this paper, we propose a new cellular botnet named SoCellBot that exploits online social networks (OSNs) to recruit bots and uses OSN messaging systems as communication channels between bots. Our proposed botnet is the first that uses the...
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