  Website Fingerprinting (WF) attacks are used by passive, local attackers to
determine the destination of encrypted internet traffic by comparing the
sequences of packets sent to and received by the user to a previously recorded
data set. As a result, WF attacks are of particular concern to
privacy-enhancing technologies such as Tor. In response, a variety of WF
defenses have been developed, though they tend to incur a high bandwidth and
latency overhead or require additional infrastructure, making them difficult to
implement in practice. Some lighter-weight defenses have been presented as
well; still, they attain only moderate effectiveness against recently published
WF attacks. In this paper, we aim to present a realistic and novel defense,
Regulator, that demonstrates improved overhead and high effectiveness against
current WF attacks. In the closed-world setting, this defense reduces the
accuracy of the state-of-the-art attack, Tik-Tok, against lightweight defenses
from 66% to 22.9%. To achieve this performance, it requires minimal added
latency and a bandwidth overhead 38.1% less than the leading lightweight
defense. In the open-world setting, Regulator limits a precision-tuned Tik-Tok
attack to an F-score of .087, compared to .625 for the best comparable
lightweight defense.
