Abstract
To improve the security of network sensitive information transmission and storage, it is necessary to design the anti-tampering monitoring of network sensitive information, and a tamper-proof monitoring technology of network sensitive information in big data environment based on big data dimension feature block is proposed. Big data feature space reconstruction method is used to calculate the grid density of network sensitive information distribution, and the network sensitive information to be tampered-proof monitoring is mapped to the divided high-dimensional phase space through the density threshold. The high dimensional phase space of information distribution is divided into dense unit and sparse unit. The coded key is matched to the corresponding network sensitive information block to realize information encryption and covert communication. The simulation results show that the information steganography performance of network sensitive information transmission and storage using this information tampering monitoring technology is better, and the information security transmission ability is improved.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Shen, Y., Zhang, L. (2019). Anti-tampering Monitoring Method of Network Sensitive Information Based on Big Data Analysis. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 302. Springer, Cham. https://doi.org/10.1007/978-3-030-36405-2_9
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DOI: https://doi.org/10.1007/978-3-030-36405-2_9
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-030-36405-2
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