VeriStream - A Framework for Verifiable Data Streaming
نویسندگان
چکیده
In a Verifiable Data Streaming (VDS) protocol a computationally weak client outsources his storage to an untrusted storage provider. Later, the client can efficiently append and update data elements in the already outsourced and authenticated data set. Other users can stream arbitrary subsets of the authenticated data and verify their integrity on-the-fly, using the data owner’s public verification key. In this work, we present VeriStream, a fully-fledged open source framework for verifiable data streaming with integration into Dropbox. At its core, our framework is based upon a novel construction of an authenticated data structure, which is the first one that allows verifiable data streams of unbounded length and at the same time outperforms the best known constructions in terms of bandwidth and computational overhead. We provide a detailed performance evaluation, showing that VeriStream only incurs a small bandwidth overhead, while providing various security guarantees, such as freshness, integrity, authenticity, and public verifiability, at the same time.
منابع مشابه
Design and Test of the Real-time Text mining dashboard for Twitter
One of today's major research trends in the field of information systems is the discovery of implicit knowledge hidden in dataset that is currently being produced at high speed, large volumes and with a wide variety of formats. Data with such features is called big data. Extracting, processing, and visualizing the huge amount of data, today has become one of the concerns of data science scholar...
متن کاملFuzzy Data Envelopment Analysis for Classification of Streaming Data
The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...
متن کاملFuzzy Data Envelopment Analysis for Classification of Streaming Data
The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...
متن کاملStreaming Authenticated Data Structures
We consider the problem of streaming verifiable computation, where both a verifier and a prover observe a stream of n elements x1, x2, . . . , xn and the verifier can later delegate some computation over the stream to the prover. The prover must return the output of the computation, along with a cryptographic proof to be used for verifying the correctness of the output. Due to the nature of the...
متن کاملClassification of Streaming Fuzzy DEA Using Self-Organizing Map
The classification of fuzzy data is considered as the most challenging areas of data analysis and the complexity of the procedures has been obstacle to the development of new methods for fuzzy data analysis. However, there are significant advances in modeling systems in which fuzzy data are available in the field of mathematical programming. In order to exploit the results of the researches on ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015