Transparency Logs via Append-Only Authenticated Dictionaries

Transparency Logs via Append-Only Authenticated Dictionaries
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DOI:
10.1145/3319535.3345652
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发表时间:
2019-11
期刊:
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security
影响因子:
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通讯作者:
Alin Tomescu;Vivek Bhupatiraju;D. Papadopoulos;Charalampos Papamanthou;Nikos Triandopoulos;S. Devadas
Alin Tomescu;Vivek Bhupatiraju;D. Papadopoulos;Charalampos Papamanthou;Nikos Triandopoulos;S. Devadas
中科院分区:
其他
文献类型:
--
作者:
Alin Tomescu;Vivek Bhupatiraju;D. Papadopoulos;Charalampos Papamanthou;Nikos Triandopoulos;S. Devadas

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透明日志允许用户审计潜在的恶意服务,为更负责任的互联网铺平道路。例如,证书透明(CT)使域所有者能够审计证书颁发机构(ca)并检测模拟攻击。然而,为了充分发挥其潜力,透明度日志在用户查询时必须具有带宽效率。具体来说,每个人都应该能够通过他们的键有效地查找日志条目,并有效地验证日志是否仍然是仅挂起的。不幸的是,如果没有额外的信任假设,当前的透明度日志不能同时提供小规模的查找证明和小规模的仅追加证明。事实上,其中一种证明总是要求带宽与日志大小呈线性关系,这使得每个人查询日志的成本都很高。在本文中,我们使用一种新的原语来解决这一问题,该原语称为仅追加身份验证字典(AAD)。我们的构造是第一个实现两种证明类型的(多)对数大小,并有助于减少透明度日志中的带宽消耗。这是以增加附加时间和高内存使用量为代价的,这两个方面都有待改进,以使实际部署成为可能。
Transparency logs allow users to audit a potentially malicious service, paving the way towards a more accountable Internet. For example, Certificate Transparency (CT) enables domain owners to audit Certificate Authorities (CAs) and detect impersonation attacks. Yet, to achieve their full potential, transparency logs must be bandwidth-efficient when queried by users. Specifically, everyone should be able to efficientlylook up log entries by their keyand efficiently verify that the log remainsappend-only. Unfortunately, without additional trust assumptions, current transparency logs cannot provide both small-sizedlookup proofs and small-sizedappend-only proofs. In fact, one of the proofs always requires bandwidth linear in the size of the log, making it expensive for everyone to query the log. In this paper, we address this gap with a new primitive called anappend-only authenticated dictionary (AAD). Our construction is the first to achieve (poly)logarithmic size for both proof types and helps reduce bandwidth consumption in transparency logs. This comes at the cost of increased append times and high memory usage, both of which remain to be improved to make practical deployment possible.