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"Optimal Verifiable Data Streaming Under Concurrent Queries" by Jianghong Wei, Meixia Miao et al.

The rapid development of both hardware and software has promoted the popularization of various real-time applications like health monitoring and intrusion detection that are widely deployed in outsourcing scenarios, e.g., mobile edge computing and cloud computing. In these applications, end devices continuously generate unbounded sequences of data items at a fast rate, i.e., the so-called streaming data. Nevertheless, storing and processing massive amounts of streaming data poses a challenge for resources-restricted end devices. Although outsourcing data items to edge servers or cloud servers is an attractive solution to the above problem, it also brings a new challenge, i.e., how to guarantee the integrity of outsourced data, since streaming data applications are usually sensitive of both location and the corresponding context, and servers are not completely trusted. To this end, the primitive of verifiable data streaming (VDS) protocol was introduced to maintain outsourced streaming ....

Computational Modeling , Cryptographic Accumulator , Data Auditing , Data Integrity , Multi Access Edge Computing , Utsourced Storage , Real Time Systems , Erifiable Data Streaming ,

"Optimal Verifiable Data Streaming Protocol with Data Auditing" by Jianghong Wei, Guohua Tian et al.

As smart devices connected to networks like Internet of Things and 5G become popular, the volume of data generated over time (i.e., stream data) by them is growing rapidly. As a consequence, for these resources-limited client-side devices, it becomes very challenging to store the continuously generated stream data locally. Although the cloud storage provides a perfect solution to this problem, the data owner still needs to ensure the integrity of the outsourced stream data, since various applications built upon stream data are sensitive of both its context and order. To this end, the notion of verifiable data streaming (VDS) was proposed to effectively append and update stream data outsourced to an untrusted cloud server, and has received significant attention. However, previous VDS constructions adopt Merkle hash tree to capture the integrity of outsourced data, and thus inevitably have logarithmic costs. In this paper, we further optimize the construction of VDS in terms of communica ....

Cryptographic Accumulator , Data Auditing , Utsourced Storage , Erifiable Data Streaming ,

"Verifiable data streaming with efficient update for intelligent automa" by Meixia Miao, Jianghong Wei et al.

The wide deployment of Internet of Things (IoT) devices enables the controller to continuously collect massive volume data in automation systems, and makes it possible to make intelligent decisions based on machine learning techniques. In fact, data-driven intelligent automation systems have been common in the industrial community. Nevertheless, how to effectively store the collected stream data and ensure their integrity is still challenging. To this end, the notion of verifiable data streaming (VDS) protocol, which enables a client to outsource the stream data to an untrusted server in a verifiable manner, was introduced. However, we argue that existing VDS protocols based on the chameleon authentication tree (CAT) are inefficient in the data update, since the whole CAT must be updated accordingly to avoid acute exposure of chameleon hashing. Thus, they are infeasible for intelligent automation systems that need to frequently update data. In this article, we first introduce a new pri ....

Chameleon Hash Families , Intelligent Automation Systems , Utsourced Storage , Erifiable Data Streaming ,