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—Small talk is an important social lubricant that helps people, especially strangers, initiate conversations and make friends with each other in physical proximity. However, due to difficulties in quickly identifying significant topics of common interest, real-world small talk tends to be superficial. The mass popularity of mobile phones can help improve(More)
—Malicious shellcodes are segments of binary code disguised as normal input data. Such shellcodes can be injected into a target process's virtual memory. They overwrite the process's return addresses and hijack control flow. Detecting and filtering out such shellcodes is vital to prevent damage. In this paper, we propose a new malicious shellcode detection(More)
— Worm attacks have been major security threats to the Internet. Detecting worms, especially new, unseen worms, is still a challenging problem. In this paper, we propose a new worm detection approach based on mining dynamic program executions. This approach captures dynamic program behavior to provide accurate and efficient detection against both seen and(More)
—With smartphones' meteoric growth in recent years, leaking sensitive information from them has become an increasingly critical issue. Such sensitive information can originate from smartphones themselves (e.g., location information) or from many Internet sources (e.g., bank accounts, emails). While prior work has demonstrated information flow tracking's(More)
The current 802.11i standard can provide data confidentiality, integrity and mutual authentication in enterprise Wireless Local Area Networks (WLANs). However, secure communication can only be provided after successful authentication and a robust security network association is established. In general, the wireless link layer is not protected by the current(More)
—Smart devices with built-in sensors, computational capabilities, and network connectivity have become increasingly pervasive. The crowds of smart devices offer opportunities to collectively sense and perform computing tasks in an unprecedented scale. This paper presents Crowd-ML, a privacy-preserving machine learning framework for a crowd of smart devices,(More)
—The ability to track and locate physical entities is a fundamental requirement for Cyber-Physical Systems (CPSs), especially in an ad-hoc wireless environment. In Heterogeneous Wireless Networks (HWNs), hybrid localization schemes are needed due to the coexistence of both accurate and coarse measurement mechanisms. However, current localization schemes(More)