Practical Cryptographic Forensic Tools for Lightweight Internet of Things and Cold Storage Systems
Practical Cryptographic Forensic Tools for Lightweight Internet of Things and Cold Storage Systems
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DOI：
10.1145/3576842.3582376
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发表时间：
2023-05
期刊：
影响因子：
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通讯作者：
Saif E. Nouma;A. Yavuz
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文献类型：
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作者：
Saif E. Nouma;A. Yavuz
物联网（IoT）和物联网即服务（STaaS）连续体允许通过云系统对IoT设备收集的安全敏感信息进行经济高效的维护。在IoT-STaaS应用中，必须保证敏感数据的安全性。特别是，日志条目跟踪计算机系统中的关键事件，并在IoT-STaaS的可信度中发挥着至关重要的作用。理想的日志保护工具必须是可扩展的，轻量级的，适用于大量资源有限的物联网设备，同时允许在STaaS上进行有效和公开的验证。然而，现有的加密日志记录方案要么给日志记录器带来显著的计算/签名开销，要么给云带来极大的存储和验证成本。迫切需要一种加密取证日志工具，以满足IoT-STaaS连续体的效率要求。在本文中，我们为日志创建了新的数字签名，称为Optimal Signatures for secure Logging（），这是第一个（据我们所知）提供小常数签名和公钥大小的数字签名，通过各种粒度提供接近最佳的签名和批量验证。我们引入了新的设计功能，如一次性的随机性管理，灵活的聚合沿着与各种优化，以同时达到这些看似冲突的属性。我们的实验表明，提供了50倍的速度比最紧凑的替代方案具有相同的签名大小的验证（235个条目），同时也是几个数量级的更紧凑，比其最有效的日志记录器。这些属性是IoT-STaaS的理想选择，其中轻量级日志记录和有效的批量验证对于物联网边缘和冷存储服务器分别至关重要。
Internet of Things (IoT) and Storage-as-a-Service (STaaS) continuum permit cost-effective maintenance of security-sensitive information collected by IoT devices over cloud systems. It is necessary to guarantee the security of sensitive data in IoT-STaaS applications. Especially, log entries trace critical events in computer systems and play a vital role in the trustworthiness of IoT-STaaS. An ideal log protection tool must be scalable and lightweight for vast quantities of resource-limited IoT devices while permitting efficient and public verification at STaaS. However, the existing cryptographic logging schemes either incur significant computation/signature overhead to the logger or extreme storage and verification costs to the cloud. There is a critical need for a cryptographic forensic log tool that respects the efficiency requirements of the IoT-STaaS continuum. In this paper, we created novel digital signatures for logs called Optimal Signatures for secure Logging (), which are the first (to the best of our knowledge) to offer both small-constant signature and public key sizes with near-optimal signing and batch verification via various granularities. We introduce new design features such as one-time randomness management, flexible aggregation along with various optimizations to attain these seemingly conflicting properties simultaneously. Our experiments show that offers 50 × faster verification (for 235 entries) than the most compact alternative with equal signature sizes, while also being several magnitudes of more compact than its most logger efficient counterparts. These properties make an ideal choice for the IoT-STaaS, wherein lightweight logging and efficient batch verification of massive-size logs are vital for the IoT edge and cold storage servers, respectively.