scholarly journals SGX-Tor: A Secure and Practical Tor Anonymity Network With SGX Enclaves

2018 ◽  
Vol 26 (5) ◽  
pp. 2174-2187 ◽  
Author(s):  
Seongmin Kim ◽  
Juhyeng Han ◽  
Jaehyeong Ha ◽  
Taesoo Kim ◽  
Dongsu Han
Keyword(s):  
2020 ◽  
Vol 117 (50) ◽  
pp. 31716-31721
Author(s):  
Eric Jardine ◽  
Andrew M. Lindner ◽  
Gareth Owenson

The Tor anonymity network allows users to protect their privacy and circumvent censorship restrictions but also shields those distributing child abuse content, selling or buying illicit drugs, or sharing malware online. Using data collected from Tor entry nodes, we provide an estimation of the proportion of Tor network users that likely employ the network in putatively good or bad ways. Overall, on an average country/day, ∼6.7% of Tor network users connect to Onion/Hidden Services that are disproportionately used for illicit purposes. We also show that the likely balance of beneficial and malicious use of Tor is unevenly spread globally and systematically varies based upon a country’s political conditions. In particular, using Freedom House’s coding and terminological classifications, the proportion of often illicit Onion/Hidden Services use is more prevalent (∼7.8%) in “free” countries than in either “partially free” (∼6.7%) or “not free” regimes (∼4.8%).


Author(s):  
Florian Platzer ◽  
Marcel Schäfer ◽  
Martin Steinebach

Tor is a widely-used anonymity network with more than two million daily users. A prominent feature of Tor is the hidden service architecture. Hidden services are a popular method for communicating anonymously or sharing web contents anonymously. For security reasons, in Tor all data packets to be send over the network are structured completely identical. They are encrypted using the TLS protocol and its size is fixed to exactly 512 bytes. In this work we describe a method to deanonymize any hidden service on Tor based on traffic analysis. This method allows an attacker with modest resources to deanonymize any hidden services in less than 12.5 days. This poses a threat to anonymity online.


Author(s):  
Benjamin Fabian ◽  
Florian Goertz ◽  
Steffen Kunz ◽  
Sebastian Müller ◽  
Mathias Nitzsche

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