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Online social networks, which have been expanding at a blistering speed recently, have emerged as a popular communication infrastructure for Internet users. Meanwhile, malware that specifically target these online social networks are also on the rise. In this work, we aim to investigate the characteristics of malware propagation in online social networks.(More)
Proximity-based mobile social networking (PMSN) refers to the social interaction among physically proximate mobile users directly through the Bluetooth/WiFi interfaces on their smartphones or other mobile devices. It becomes increasingly popular due to the recently explosive growth of smartphone users. Profile matching means two users comparing their(More)
The widely popular browser extensions now become one of the most commonly used malware attack vectors. The Google Chrome browser, which implements the principles of least privileges and privilege separation by design, offers a strong security mechanism to protect malicious websites from damaging the whole browser system via extensions. In this study, we(More)
With their blistering expansions in recent years, popular on-line social sites such as Twitter, Facebook and Bebo, have become some of the major news sources as well as the most effective channels for viral marketing nowadays. However, alongside these promising features comes the threat of misinformation propagation which can lead to undesirable effects,(More)
Bot-like malware has posed an immense threat to computer security. Bot detection is still a challenging task since bot developers are continuously adopting advanced techniques to make bots more stealthy. A typical bot exhibits three invariant features along its onset: (1) the startup of a bot is automatic without requiring any user actions; (2) a bot must(More)
The alarm that worms start to spread on increasingly popular mobile devices calls for an in-depth investigation of their propagation dynamics. In this paper, we study how mobility patterns affect Bluetooth worm spreading speeds. We find that the impact of mobility patterns is substantial over a large set of of changing Bluetooth and worm parameters. For(More)
In this work, we explore techniques that can automatically classify malware variants into their corresponding families. Our framework extracts structural information from malware programs as attributed function call graphs, further learns discriminant malware distance metrics, finally adopts an ensemble of classifiers for automated malware classification.(More)
TCP is the most widely used transport layer protocol used in the Internet today. A TCP session adapts the demands it places on the network to observations of bandwidth availability on the network. Because TCP is adaptive, any model of its behavior that aspires to be accurate must be influenced by other network traffic. This point is especially important in(More)
Characterizing what makes a packet reordering metric meaningful is a problem that has attracted significant interest, but it still lacks a universally accepted solution. We contribute to this discussion by investigating some theoretical concepts that make the following simple intuitions precise: (1) a metric that is inconsistent, i.e., gives different(More)