Multimedia applications in smart electronic commerce (e-commerce), such as online trading and Internet marketing, always face security in storage and transmission of digital images and videos. This study addresses the problem of security in e-commerce and proposes a unified framework to analyze the security data. First, to allocate the definite security resources optimally, we build our e-commerce monitoring model as an undirected network, where a monitored node is a vertex of the graph and a connection between vertices is an undirected edge. Moreover, we aim to find a minimal cover for the monitoring network as the optimal solution of resource allocation, which is defined as the network monitoring minimization problem (NMM). This problem is proved to be NP-hard. Second, by analyzing the latent threats, we design a novel and trusted monitoring system that can integrate incident monitoring, data analysis, risk assessment, and security warnings. This system does not touch users’ privacy data. Third, we propose a sequential model-based risk assessment method, which can predict the risk according to the text semantics. Our experimental results on web scale data demonstrate that our system is flexible enough when monitoring, which also verify the effectiveness and efficiency of our system.
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