Abstract
Internet circumvention applications – such as Psiphon – are widely used to bypass control mechanisms, and each of such anti-censorship application uses a unique mechanism to bypass internet censorship. Although anti-censorship applications provide a unique means to ensure internet freedom, some applications severely degrade network performance and possibly open the door for network security breaches. Anti-censorship applications such as Psiphon can be used as cover for hacking attempts and can assist in many criminal activities. In this paper, we analyze the Psiphon service and perform a passive traffic analysis to detect Psiphon traffic. Moreover, we profile the top 100 websites based on their Alexa rankings according to five different categories under Psiphon and perform an effective website fingerprinting attack. Our analysis uses the well-known k-nearest neighbors for website fingerprinting and support vector machine classifier to detect Psiphon traffic.
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Ejeta, T.G., Kim, H.J. (2017). Website Fingerprinting Attack on Psiphon and Its Forensic Analysis. In: Kraetzer, C., Shi, YQ., Dittmann, J., Kim, H. (eds) Digital Forensics and Watermarking. IWDW 2017. Lecture Notes in Computer Science(), vol 10431. Springer, Cham. https://doi.org/10.1007/978-3-319-64185-0_4
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DOI: https://doi.org/10.1007/978-3-319-64185-0_4
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