Abstract: With the prosperous development of Web services, protecting Web-surfing privacy has become a significant concern to society. Various protection techniques (e.g., anonymous communication networks) have been proposed to help users hide the real access targets and anonymously browse the Internet. However, Webpage fingerprinting (WF) identifications, through monitoring and analyzing network traffic, can still determine whether a Web page is visited by exploiting network traffic features, thus jeopardizing the anonymity. On the other hand, law enforcement agencies can leverage the methods of WF identification to monitor anonymous networks to prevent abusing them for carrying out illegal activities or covering up crimes. Therefore, WF identification is a significant and noteworthy technique for privacy protection and network supervision. In this survey, we first introduce the concept and development of WF identifications, and then focus on two kinds of WF identifications on Tor, a widely used anonymous network, including single-tag oriented identifications and multi-tag oriented identifications. In particular, the characteristics of these WF identifications are analyzed and these WF limitations are pointed out, such as simplistic assumptions and insufficient experiments for systematical evaluation. Finally, future research directions for WF identifications are concluded.

Key words: Webpage fingerprinting identification, Tor anonymous communication, privacy preserving, traffic analysis, machine learning, network supervision