  Tor recently integrated a circuit padding framework for creating padding
machines: defenses that work by defining state machines that inject dummy
traffic to protect against traffic analysis attacks like Website Fingerprinting
(WF) attacks. In this paper, we explore the design of effective and efficient
padding machines to defend against WF attacks. Through the use of carefully
crafted datasets, a circuit padding simulator, genetic programming, and manual
tuning of padding machines we explore different aspects of what makes padding
machines effective and efficient defenses. Our final machine, named Interspace,
is probabilistically-defined with a tweakable trade-off between efficiency and
effectiveness against the state-of-the-art deep-learning WF attack Deep
Fingerprinting by Sirinam et al. We show that Interspace can be both more
effective and efficient than WTF-PAD by Juarez et al. the padding machine that
inspired the design of Tor's circuit padding framework. We end this paper by
showing how Interspace can be made less effective, identifying the promising
tactic of probabilistically defined padding machines, and highlighting the need
to further explore this tactic in more complex defenses.
