Detecting fake accounts in online social networks (OSNs) protects OSN operators and their
users from various malicious activities. Most detection mechanisms attempt to predict and …

Detecting fake accounts in online social networks (OSNs) protects both OSN operators and
their users from various malicious activities. Most detection mechanisms attempt to classify …

Online social networks (OSNs) attract attackers that use abusive accounts to conduct
malicious activities for economic, political, and personal gain. In response, OSNs often …

Users increasingly rely on the trustworthiness of the information exposed on Online Social
Networks (OSNs). In addition, OSN providers base their business models on the …

Users increasingly rely on crowdsourced information, such as reviews on Yelp and Amazon,
and liked posts and ads on Facebook. This has led to a market for blackhat promotion …

Fake accounts are a preferred means for malicious users of online social networks to send
spam, commit fraud, or otherwise abuse the system. A single malicious actor may create …

In this paper, we study the problem of early detection of fake user accounts on social
networks based solely on their network connectivity with other users. Removing such …

Online social networks (OSNs) suffer from the creation of fake accounts that introduce fake
product reviews, malware and spam. Existing defenses focus on using the social graph …

Online social networks are plagued by fake information. In particu-lar, using massive fake
accounts (also called Sybils), an attacker can disrupt the security and privacy of benign …

Account compromization is a serious threat to users of online social networks (OSNs). While
relentless spammers exploit the established trust relationships between account owners and …