2019-nasr-enemy
findings extracted from this paper
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A proxy assignment algorithm derived from the Gale-Shapley college admissions game, using multi-feature utility functions across five client metrics (proxy utilization capped at T, new-proxy request rate, blocked-proxy usage, known-blocked count, client distance) achieves superior connected-client ratios and lower wait times compared to state-of-the-art rBridge in all tested ecosystem configurations (Static, Slow, Alive, Popular), without requiring knowledge of individual client types at assignment time.
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The Chinese GFW enumerated all Tor bridges within approximately one month by deploying censoring agents that impersonated regular users, demonstrating that CAPTCHA- and email-based proxy distribution mechanisms are ineffective against resourceful state-level censors who can create large numbers of accounts and use human-based CAPTCHA-solving platforms.
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Omnipresent censors who distribute censoring agents across diverse geographic locations obtain significantly more proxies than circumscribed censors confined to a single subnet, because location diversity improves their utility scores in proximity-weighted proxy assignment systems.
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A game-theoretic optimal censorship strategy — in which coordinated agents maximize a joint utility combining proxy discovery and blocking impact (equation 3, parameterized by ω) — is significantly stronger than both aggressive (immediate block) and conservative (timed-delay) heuristic strategies evaluated in prior work including rBridge; changing ω (surveillance vs. blocking preference) further modulates the damage a censor can inflict on any given distribution profile.
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In a static proxy pool (λ=0, no new proxies added), the fraction of connected censored clients decreases monotonically to near zero regardless of censorship strategy, even at low censoring-agent fractions (ρ=0.05) and against a non-strategic aggressive censor with a strict-balanced distributor profile.