Security data transmission method based on compressive sensing theory

A technology of secure data and compressed sensing, applied in the field of secure data transmission, can solve problems that have not been applied to ensure the security of data transmission, reduce the number of data transmission, etc., and achieve the effect of perfecting confidentiality
CN102938698AInactive Publication Date: 2013-02-20东北大学秦皇岛分校
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
东北大学秦皇岛分校
Publication Date
2013-02-20
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention relates to a method for achieving security data transmission by utilizing a compressive sensing theory. Currently, the compressive sensing theory has not been applied to guaranteeing security of data transmission between a source end and a destination end in a data communication process. The source end is encrypted by a random projection matrix and a random vector, and the destination end is decrypted by the sub-matrix of the left zero matrix of the random projection matrix to re-construct data to be transmitted. Mutual information attribute in an information theory is used to prove that the data transmission method disclosed by the invention has perfect security, i.e., the method is safe to a ciphertext-only attack. The method is not only applicable to a point-to-point communication, but also applicable to multipoint-to-point communication and multipoint-to-multipoint communication. Especially when computing power of the data source end and the destination end is asymmetric (in such application fields as internet of things, wireless sensor network and the like), the method has greater advantages.
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Description

technical field

[0001] The invention relates to a method for realizing secure data transmission by using compressed sensing theory, in particular to a method for using random vector projection encryption, minimum l 0 The secure data transmission method decrypted by the norm optimization method can be applied to the secure data transmission between the source end and the destination end in the data communication process. Background technique

[0002] Most of the current data acquisition systems are designed based on the traditional Shannon sampling theorem, that is, in order to avoid signal distortion, the sampling frequency must not be lower than twice the highest frequency of the signal. However, there is a large redundancy in the data collected in this way, especially in image, video and other application fields, a large amount of collected data greatly increases the cost of data transmission and storage. In recent years, compressive sensing theory has brought revolutiona...

Claims

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