Ian Martiny (University of Colorado Boulder), Gabriel Kaptchuk (Boston University), Adam Aviv (The George Washington University), Dan Roche (U.S. Naval Avademy), Eric Wustrow (University of Colorado Boulder)

The Signal messaging service recently deployed a emph{sealed sender} feature that provides sender anonymity by cryptographically hiding a message's sender from the service provider. We demonstrate, both theoretically and empirically, that this one-sided anonymity is broken when two parties send multiple messages back and forth; that is, the promise of sealed sender does not emph{compose} over a conversation of messages. Our attack is in the family of Statistical Disclosure Attacks (SDAs), and is made particularly effective by emph{delivery receipts} that inform the sender that a message has been successfully delivered, which are enabled by default on Signal. We show using theoretical and simulation-based models that Signal could link sealed sender users in as few as 5 messages.

Our attack goes beyond tracking users via network-level identifiers by working at the application layer of Signal. This make our attacks particularly effective against users that employ Tor or VPNs as anonymity protections, who would otherwise be secure against network tracing. We present a range of practical mitigation strategies that could be employed to prevent such attacks, and we prove our protocols secure using a new simulation-based security definition for one-sided anonymity over any sequence of messages. The simplest provably-secure solution uses many of the same mechanisms already employed by the (flawed) sealed-sender protocol used by Signal, which means it could be deployed with relatively small overhead costs; we estimate that the extra cryptographic cost of running our most sophisticated solution in a system with millions of users would be less than $40 per month.

View More Papers

From WHOIS to WHOWAS: A Large-Scale Measurement Study of...

Chaoyi Lu (Tsinghua University; Beijing National Research Center for Information Science and Technology), Baojun Liu (Tsinghua University; Beijing National Research Center for Information Science and Technology; Qi An Xin Group), Yiming Zhang (Tsinghua University; Beijing National Research Center for Information Science and Technology), Zhou Li (University of California, Irvine), Fenglu Zhang (Tsinghua University), Haixin Duan…

Read More

Trust the Crowd: Wireless Witnessing to Detect Attacks on...

Kai Jansen (Ruhr University Bochum), Liang Niu (New York University), Nian Xue (New York University), Ivan Martinovic (University of Oxford), Christina Pöpper (New York University Abu Dhabi)

Read More