Online Social Network (OSN) platforms are growing regularly and they keep on attracting users from all over the world. However, OSN actively and voluntarily collect data about their users at an exponential rate, jeopardizing their right to privacy. Additionally, people willingly disclose and share their personal information, exacerbating the issue. Malicious third parties piggyback on this data sharing and increase the risk of anyone becoming the victim of deception. Even technologically knowledgeable people, concerned for their privacy, have been trapped, due to of the numerous online deception techniques. In addition, the rise of new technologies used to deceive people in OSN, makes the need for privacy protection more crucial than ever because OSN is bringing new choices, new opportunities, but also new dangers. As such, various researchers keep on working and deriving innovative techniques to detect and prevent online deception. In this work, we propose a taxonomy to help coordinate and organize the efforts of protecting OSN users against online deception. To build the taxonomy, first we conducted a survey of the various online deception techniques and their corresponding countermeasures. Then we organized and grouped them into different categories to derive our taxonomy.
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