arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2201.11860cs.CR
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加密货币对等网络安全方案的安全性研究

On the Anonymity of Peer-To-Peer Network Anonymity Schemes Used by Cryptocurrencies

Piyush Kumar Sharma, Devashish Gosain, Claudia Diaz

摘要:

加密货币系统可以通过利用其对等网络上的网络级通信来遭受去匿名化攻击。控制对等网络中一组共谋节点的对手可以观察正在交换的交易并推断所涉及的各方。因此,已经提出了各种网络匿名方案来缓解这个问题,其中一些解决方案提供了理论上的匿名保证。在这项工作中,我们这样的对等网络匿名解决方案的模型,并评估其匿名保证。为此,我们提出了一个新的框架,使用贝叶斯推理,以获得概率分布连接交易,他们可能的发起人。我们用这些分布来描述交易匿名性,用熵作为发起者身份的对抗性不确定性的度量。特别是,我们为Danvis、Danvis ++和Lightning Network建模。我们研究了不同的配置,并证明他们都没有提供可接受的匿名用户。例如,我们的分析显示,在广泛部署的闪电网络中,有1%的战略选择的共谋节点,对手可以唯一地确定网络中约50%的交易的发起者。在丹麦,控制15%节点的对手平均只有8个可能的发起者。此外,我们观察到,由于Danvis和Danvis ++的设计方式,增加网络规模并不对应于潜在发起者的匿名集合的增加。令人担忧的是,我们对闪电网络的纵向分析揭示了一个相反的趋势--随着网络的发展,整体匿名性下降。

英文摘要:

Cryptocurrency systems can be subject to deanonimization attacks by exploiting the network-level communication on their peer-to-peer network. Adversaries who control a set of colluding node(s) within the peer-to-peer network can observe transactions being exchanged and infer the parties involved. Thus, various network anonymity schemes have been proposed to mitigate this problem, with some solutions providing theoretical anonymity guarantees. In this work, we model such peer-to-peer network anonymity solutions and evaluate their anonymity guarantees. To do so, we propose a novel framework that uses Bayesian inference to obtain the probability distributions linking transactions to their possible originators. We characterize transaction anonymity with those distributions, using entropy as metric of adversarial uncertainty on the originator's identity. In particular, we model Dandelion, Dandelion++ and Lightning Network. We study different configurations and demonstrate that none of them offers acceptable anonymity to their users. For instance, our analysis reveals that in the widely deployed Lightning Network, with 1% strategically chosen colluding nodes the adversary can uniquely determine the originator for about 50% of the total transactions in the network. In Dandelion, an adversary that controls 15% of the nodes has on average uncertainty among only 8 possible originators. Moreover, we observe that due to the way Dandelion and Dandelion++ are designed, increasing the network size does not correspond to an increase in the anonymity set of potential originators. Alarmingly, our longitudinal analysis of Lightning Network reveals rather an inverse trend -- with the growth of the network the overall anonymity decreases.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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