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In cloud data center, shared storage with good management is a main structure used for the storage of virtual machines (VM). In this paper, we proposed Hybrid VM storage (HVSTO), a privacy preserving shared storage system designed for the virtual machine storage in large-scale cloud data center. Unlike traditional shared storage, HVSTO adopts a distributed structure to preserve privacy of virtual...
Nowadays the amount of data is being produced exponentially with the rapid development of electronic technology and communication, which makes it hard to cost-effectively store and manage these big data. Cloud computing, a new business model, is considered as one of most attractive solutions for big data, and provides the advantage of reduced cost through sharing of computing and storage resources...
With the explosive growth of web-based cameras and mobile devices, billions of photographs are uploaded to the internet. We can trivially collect a huge number of photo streams for various goals, such as 3D scene reconstruction and other big data applications. However, this is not an easy task due to the fact the retrieved photos are neither aligned nor calibrated. Furthermore, with the occlusion...
In the era of big data, many users and companies start to move their data to cloud storage to simplify data management and reduce data maintenance cost. However, security and privacy issues become major concerns because third-party cloud service providers are not always trusty. Although data contents can be protected by encryption, the access patterns that contain important information are still exposed...
Information centric networking (ICN) architectures represent a conceptual shift from naming end-hosts in the Internet to naming content directly, and require either significant changes to the existing IP infrastructure or replacing it entirely. We present iDNS (information-centric DNS), an evolutionary path towards deploying ICN at Internet scale based on modifications to the DNS that leave the current...
Anomaly detection is essential for preventing network outages and maintaining the network resources available. However, to cope with the increasing growth of Internet traffic, network anomaly detectors are only exposed to sampled traffic, so harmful traffic may avoid detector examination. In this paper, we investigate the benefits of recent distributed computing approaches for real-time analysis of...
In this paper, a framework for anomaly detection and forensics in Big Data is introduced. The framework tackles the Big Data 4 Vs: Variety, Veracity, Volume and Velocity. The varied nature of the data sources is treated by transforming the typically unstructured data into a highly dimensional and structured data set. To overcome both the uncertainty (low veracity) and high dimension introduced, a...
Content Delivery Network (CDN) improves large scale data delivery with widely distributed data replicas; But the fundamental goal of IP is to connect two hosts. As a consequence, request routing, which selects the best server to serve the requested data, is introduced to meet the mismatch between CDN and IP. In contrast to IP, Named Data Networking (NDN) makes content the first-class citizen of the...
Business Intelligence systems use information technology to supply integrated management support with data coming from several sources of structured and unstructured data. The integrated infrastructures of Business Intelligence (BI) are often too complex and hence costly and inflexible. A solution for these issues is to leverage cloud computing services to enhance legacy BI systems and applications...
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