Media audio-visual program supervision system based on network topology

Zhongfu Li () and Shikun Liu ()
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Zhongfu Li: Zaozhuang University
Shikun Liu: Zaozhuang University

International Journal of System Assurance Engineering and Management, 2021, vol. 12, issue 4, No 9, 705-717

Abstract: Abstract While media audiovisual programs have brought great convenience to people's study, work and life, there are also a lot of bad information flooding them. This research mainly discusses the design of media audio-visual program monitoring system based on network topology. The system mainly monitors audiovisual programs through the network topology scanning module. For security reasons, the system network structure is divided into two parts: internal network and external network. The supervisory system is located in the internal network and is physically separated from the external network. In the initial scanning process, first obtain the starting device information in the configuration file, which is the routing device by default, read the relevant information in the MIB through the SNMP agent, and analyze the neighboring routing device and its downstream switching devices and hosts. Information and other topological information, and transmit the topological information to the data organization and distribution module. In order to avoid a large load on the network operation of the target autonomous domain, it is recommended to scan a larger network once an hour, or you can make your own decision based on the actual situation. In order to be able to quickly and accurately discover the changes in scanned data, the system uses MD5 verification to generate a "fingerprint" for each record to identify the data. Through this algorithm, the amount of information in the database is effectively reduced, and the efficiency of retrieval is improved, and the system is optimized. In order to reduce the misjudgment of legal shadow marks in shadow marks, after verifying 10,000 sets of sample shadow mark images and adjusting the contrast recognition threshold, the missed judgement rate can be less than 2%. The system designed in this research meets the needs of program supervision.

Keywords: Network topology; MD5 video digest algorithm; Network structure; Program supervision (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s13198-021-01066-2

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