Privacy flaws create value gaps in crypto protocols and markets
Pricing the Unprovable: Ambiguity, Turnstile Runs, and the Verifiability Discount in Crypto Protocols
Cryptography and Security
Summary
Sometimes, a secret problem in encrypted digital money systems can hurt trust and value, even when no one admits they used it to steal. The authors show how uncertainty about past damage makes investors less sure how much the system's tokens are worth. They built a tool called VDISC that tracks reported losses, evidence, and money flows to analyze real cases and market reactions. Their findings help suggest ways to design better systems that clearly share how much risk remains after a fix.
What this means in practice
- •For blockchain developers: Integrate frameworks like VDISC to separately track security incidents and evidence for improved market transparency in privacy-focused blockchains.
- •For crypto asset managers: Assess and factor in the verifiability discount to better estimate risks and potential value changes in privacy-enabled cryptocurrencies.
Authors
Doohwi Cha, Hanhee Kim, Hyeonjun Yeo, Minsuk Sung, Minjae Lee, Seunghan Son, Donghwa Seo, Juyeong Lee
Abstract
Privacy-preserving protocols can repair a vulnerability without establishing whether it was exploited beforehand, even when no theft is reported and aggregate supply is protected. We call the potential value reduction from this gap the verifiability discount. A turnstile model shows how early withdrawal can shift a possible shortfall to remaining holders and why credible evidence can become more valuable as exposure grows. We introduce VDISC, a reproducible framework that records reported loss, exposed value, public evidence, returns, and pool flows separately. It combines Orchard's staged disclosures with reconstructed on-chain flows, earlier Zcash cases, and a 40-event security panel. Orchard follows the predicted direction: market responses were muted after repair and supply assurance, while the largest negative return and aggregate shielded-pool net outflow aligned with the acknowledgment that past abuse could not be ruled out. These patterns are directional, not causal. Across events, market-cap-normalized reported loss and unresolved exposure overlap among the 38 events with a public loss figure (Pearson 0.86, Spearman 0.56), partly because exposure is often coded from the loss itself, so returns alone cannot distinguish reported loss from unresolved history. The findings motivate three candidate design priorities: produce privacy-compatible evidence about past states, limit the state exposed by a single flaw, and disclose residual uncertainty explicitly.