A Novel Large-Scale Digital Forensics Service Platform for Internet Videos
A Novel Large-Scale Digital Forensics Service Platform for Internet Videos
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DOI：
10.1109/tmm.2011.2170556
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发表时间：
2012-02
影响因子：
7.3
通讯作者：
H. Yin;Wen Hui;Hongzhi Li;Chuang Lin;Wenwu Zhu
中科院分区：
文献类型：
--
作者：
H. Yin;Wen Hui;Hongzhi Li;Chuang Lin;Wenwu Zhu
越来越多的非法视频在互联网上的传输，迫使需要开发大规模的数字视频取证系统，起诉和阻止互联网上的数字犯罪。在本文中，我们提出，设计和实现了一种新的大规模数字取证服务平台（DFSP），可以有效地检测非法内容从互联网视频。更具体地说，我们提出了一个分布式架构，利用内容分发网络（CDN），以提高可扩展性，它可以处理大量的互联网视频在真实的时间。提出了一种基于CDN的资源感知调度算法（CRAS），该算法根据延迟和计算负载等资源参数在DFSP中有效地调度任务。我们在互联网上部署了DFSP系统，它集成了基于CDN的分布式架构和CRAS算法与大规模视频检测算法，并评估部署的系统。我们的评估结果证明了该平台的有效性。
The increasing transmission of illegal videos over the Internet imposes the needs to develop large-scale digital video forensics systems for prosecuting and deterring digital crimes in the Internet. In this paper, we propose, design, and implement a novel large-scale Digital Forensics Service Platform (DFSP) that can effectively detect illegal content from Internet videos. More specifically, we propose a distributed architecture by taking advantage of Content Delivery Network (CDN) to improve scalability, which can process enormous number of Internet videos in real time. We propose CDN-based Resource-Aware Scheduling (CRAS) algorithm, which schedules the tasks efficiently in the DFSP according to resource parameters, such as delay and computation load. We deploy the DFSP system in the Internet, which integrates the CDN-based distributed architecture and CRAS algorithm with a large-scale video detection algorithm, and evaluate the deployed system. Our evaluation results demonstrate the effectiveness of the platform.