TY - GEN
T1 - ProbFlow
T2 - 30th Annual Network and Distributed System Security Symposium, NDSS 2023
AU - Darir, Hussein
AU - Dullerud, Geir
AU - Borisov, Nikita
N1 - Publisher Copyright:
© 2023 30th Annual Network and Distributed System Security Symposium, NDSS 2023. All Rights Reserved.
PY - 2023
Y1 - 2023
N2 - —We present ProbFlow, a probabilistic programming approach for estimating relay capacities in the Tor network. We refine previously derived probabilistic model of the network to take into account more of the complexity of the real-world Tor network. We use this model to perform inference in a probabilistic programming language called NumPyro which allows us to overcome the analytical barrier present in purely analytical approach. We integrate the implementation of ProbFlow to the current implementation of capacity estimation algorithms in the Tor network. We demonstrate the practical benefits of ProbFlow by simulating it in flow-based Python simulator and packet-based Shadow simulations, the highest fidelity simulator available for the Tor network. In both simulators, ProbFlow provides significantly more accurate estimates that results in improved user performance, with average download speeds increasing by 25% in the Shadow simulations.
AB - —We present ProbFlow, a probabilistic programming approach for estimating relay capacities in the Tor network. We refine previously derived probabilistic model of the network to take into account more of the complexity of the real-world Tor network. We use this model to perform inference in a probabilistic programming language called NumPyro which allows us to overcome the analytical barrier present in purely analytical approach. We integrate the implementation of ProbFlow to the current implementation of capacity estimation algorithms in the Tor network. We demonstrate the practical benefits of ProbFlow by simulating it in flow-based Python simulator and packet-based Shadow simulations, the highest fidelity simulator available for the Tor network. In both simulators, ProbFlow provides significantly more accurate estimates that results in improved user performance, with average download speeds increasing by 25% in the Shadow simulations.
UR - http://www.scopus.com/inward/record.url?scp=85180623334&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85180623334&partnerID=8YFLogxK
U2 - 10.14722/ndss.2023.24140
DO - 10.14722/ndss.2023.24140
M3 - Conference contribution
AN - SCOPUS:85180623334
T3 - 30th Annual Network and Distributed System Security Symposium, NDSS 2023
BT - 30th Annual Network and Distributed System Security Symposium, NDSS 2023
PB - The Internet Society
Y2 - 27 February 2023 through 3 March 2023
ER -