CN110708512A - Intelligent household wireless network image encryption transmission optimization method - Google Patents

Intelligent household wireless network image encryption transmission optimization method Download PDF

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CN110708512A
CN110708512A CN201910986630.3A CN201910986630A CN110708512A CN 110708512 A CN110708512 A CN 110708512A CN 201910986630 A CN201910986630 A CN 201910986630A CN 110708512 A CN110708512 A CN 110708512A
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image
wireless network
intelligent home
home wireless
steps
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李星瑶
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Yantai Aiyi New Energy Co Ltd
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Yantai Aiyi New Energy Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
    • H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/44—Secrecy systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/625—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using discrete cosine transform [DCT]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/009—Security arrangements; Authentication; Protecting privacy or anonymity specially adapted for networks, e.g. wireless sensor networks, ad-hoc networks, RFID networks or cloud networks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/03—Protecting confidentiality, e.g. by encryption
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/04—Key management, e.g. using generic bootstrapping architecture [GBA]
    • H04W12/043—Key management, e.g. using generic bootstrapping architecture [GBA] using a trusted network node as an anchor
    • H04W12/0431—Key distribution or pre-distribution; Key agreement
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
  • Multimedia (AREA)
  • Computer Security & Cryptography (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • Discrete Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

The invention discloses an intelligent household wireless network image encryption transmission optimization method. The method mainly comprises the following steps: A. establishing an intelligent home wireless network topology model, acquiring a monitoring video image, and preprocessing the image; B. performing discrete cosine transform on the processed image, quantizing the coefficient of the processed image, and performing image coding by searching the code word with the minimum distance; C. the method comprises the steps that an n-dimensional hypercube is used for coding nodes of the intelligent home wireless network, a bivariate polynomial is selected as a secret key to be distributed to each node, and safe transmission is guaranteed through a matched secret key; D. and constructing an optimal path for image transmission through the n-dimensional hypercube to complete encryption transmission optimization of the intelligent home wireless network image. The method has the advantages of good adaptivity and stability, high network security connectivity, strong survivability, high image compression efficiency, high transmission speed, capability of preventing personal privacy leakage, saving energy of sensor nodes, capability of watching and operating all monitoring pictures in a home at the first time and guarantee of personal and property safety.

Description

Intelligent household wireless network image encryption transmission optimization method
Technical Field
The invention relates to an intelligent household wireless network image encryption transmission optimization method, and belongs to the field of intelligent household, image coding and routing algorithms.
Background
With the improvement and popularity of video monitoring systems, remote video monitoring systems have become an important component of smart homes. The existing intelligent home monitoring system has a short transmission distance, can only transmit signals indoors in a short distance, is insufficient in safety of a transmission network, reveals personal privacy once the network is invaded, causes unpredictable loss, is not smooth in image transmission by the transmission signals, is not high in image transmission quality, is low in transmission speed, and cannot be known immediately once an emergency occurs.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide an intelligent home wireless network image encryption transmission optimization method with good self-adaptability and stability, which has high network security connectivity, strong survivability, high image compression efficiency, fast transmission speed, and can prevent privacy leakage, save energy of sensor nodes, and enable all monitoring pictures in a home to be watched and operated at the first time, thereby ensuring personal and property safety.
The technical scheme adopted by the invention for solving the problems comprises the following steps:
A. establishing an intelligent home wireless network topology model, acquiring a monitoring video image, and preprocessing the image;
B. performing discrete cosine transform on the processed image, quantizing the coefficient of the processed image, and performing image coding by searching the code word with the minimum distance;
C. the method comprises the steps that an n-dimensional hypercube is used for coding nodes of the intelligent home wireless network, a bivariate polynomial is selected as a secret key to be distributed to each node, and safe transmission is guaranteed through a matched secret key;
D. and constructing an optimal path for image transmission through the n-dimensional hypercube to complete encryption transmission optimization of the intelligent home wireless network image.
The invention has the beneficial effects that:
under the condition that the monitoring safety of the intelligent home is more and more important, the intelligent home monitoring system has better self-adaptability and stability, high network safety connectivity and strong survivability, prevents personal privacy from being leaked, has high image compression efficiency and high transmission speed, saves the energy of sensor nodes, can watch and operate all monitoring pictures in the home at the first time, and guarantees the personal and property safety.
Drawings
FIG. 1 is an overall flow chart of an image encryption transmission optimization method for an intelligent home wireless network
FIG. 2 is a diagram of a wireless network topology model of an intelligent home
FIG. 3 image encoding flow chart
FIG. 4 is a diagram of a four-dimensional hypercube network model.
Detailed Description
Referring to fig. 1 to 4, the method of the present invention includes the steps of:
A. establishing an intelligent home wireless network topology model, acquiring a monitoring video image, and preprocessing the image;
(1) and establishing an intelligent household wireless network topology model as shown in fig. 2. The network mainly comprises a plurality of wireless sensor nodes, a wireless execution device, a wireless control center and user equipment, wherein the wireless sensor nodes comprise cameras distributed in an area needing to be monitored and are responsible for data acquisition; the wireless execution device is responsible for starting functions of sound-light alarm, camera monitoring and the like; the wireless control center processes the information from the wireless sensor nodes and transmits the information to the user equipment.
(2) Obtaining a size ofMonitoring video image
Figure 977345DEST_PATH_IMAGE002
And removing noise in the image. The pixel gray value depends on the weighted average of the neighboring pixel gray values, and the weight coefficient is:
Figure 605772DEST_PATH_IMAGE004
Figure 969758DEST_PATH_IMAGE006
wherein,
Figure DEST_PATH_IMAGE007
is the coordinate of the pixel point and is,
Figure 330332DEST_PATH_IMAGE008
is the difference in the gray value of the pixel,
Figure DEST_PATH_IMAGE009
is the standard deviation of the noise distribution and,
Figure 785627DEST_PATH_IMAGE010
the standard deviation of the pixel distance distribution,
Figure DEST_PATH_IMAGE011
is the standard deviation of the pixel gray scale difference distribution. If the gray value of the pixel point is greatly different from the neighboring gray value,
Figure 217746DEST_PATH_IMAGE012
approaching 0, which indicates that the point is a noise point and needs to be removed if it isApproaching 1, the point remains.
B. Performing discrete cosine transform on the processed image, quantizing the coefficient of the processed image, and performing image coding by searching the code word with the minimum distance;
(1) dividing the image into a plurality of sub-blocks, and performing discrete cosine transform on the image sub-blocks:
Figure 967713DEST_PATH_IMAGE014
Figure 576549DEST_PATH_IMAGE016
wherein,
Figure 750041DEST_PATH_IMAGE001
is image size, u =0,1, …, M-1; v =0,1, …, N-1. And obtaining a DC coefficient and an AC coefficient, namely an alternating current component and a direct current component, quantizing and sequencing the transformation coefficients to form a transformation vector. If the energy of the AC coefficient is larger than a preset threshold value, the block is a flat sliding block, otherwise, the block is a non-flat sliding block.
(2) Searching the code word with the minimum distance from the type of the transformation vector to the corresponding code book:
Figure 823039DEST_PATH_IMAGE018
wherein,
Figure DEST_PATH_IMAGE019
is the ith one of the transformed vectors,is the jth code word that is,
Figure DEST_PATH_IMAGE021
is the kth codeword and n is the number of codewords. Setting a distance thresholdIf, if
Figure 949444DEST_PATH_IMAGE024
If so, the vector is classified as the code word, and the code word index number of the vector is recorded; if it is
Figure DEST_PATH_IMAGE025
Judging whether the codebook is full, if so, searching the code word which has the least frequency and is not used in the current frame, and replacing the code word with the current vector; and if the codebook is not full, the current vector is the newly added code word. All the images are processed in this way, and the encoding of the images is completed.
C. The method comprises the steps that an n-dimensional hypercube is used for coding nodes of the intelligent home wireless network, a bivariate polynomial is selected as a secret key to be distributed to each node, and safe transmission is guaranteed through a matched secret key;
(1) the network is modeled using an n-dimensional hypercube. Setting up intelligent household wireless network with each length of n
Figure 723365DEST_PATH_IMAGE026
A node, encoded as:
Figure DEST_PATH_IMAGE044
randomly selecting 2n bivariate polynomials with the degree of t in the finite field GF (q):
Figure DEST_PATH_IMAGE050
wherein q isIs a large prime number, coefficient
Figure DEST_PATH_IMAGE052
Is a randomly selected positive integer over a finite field. The key distribution center selects a corresponding number of bivariate polynomials to distribute according to the ID length of each node, and the node with the ID length of n receives n polynomials.
(2) If m bits of the IDs of the two nodes are the same, m shared polynomials exist. The node puts the ID of other nodes needing to communicate into a sharing polynomial and calculates a communication key. Taking a four-dimensional hypercube as an example, as shown in fig. 4. If there is no shared polynomial between node A and node B, secret path negotiation key can be established, node A precedes intermediate node
Figure DEST_PATH_IMAGE054
Establishing a shared key and sending information to
Figure 192216DEST_PATH_IMAGE054
，And then establishing secret communication with the adjacent nodes for transmission until the message is transmitted to the node B. Thereby realizing the safe transmission of information.
D. And constructing an optimal path for image transmission through the n-dimensional hypercube to complete encryption transmission optimization of the intelligent home wireless network image.
(1) In the n-dimensional hypercube network, image data needs to be transmitted from a node A to a node B, and when the binary bit strings of two nodes are known, each binary bit is compared in the adjacent nodes of A in sequence, and if the binary bits are the same, the image data continues to be transmitted; if the two bits are different, the binary bit of the communication upstream node is changed to be the same as the corresponding bit of B, and after a plurality of changes, the former bits are the same.
(2) If all binary digits are the same, the optimal transmission path is determined; if the next bit can not be changed, backtracking is required. When the middle node C cannot find the next same binary digit, a path D is expanded in the cube, so that the node C can be communicated with the node B, an optimal path for image transmission is formed, and encryption transmission optimization of the intelligent home wireless network image is completed.
In conclusion, the method for optimizing the image encryption transmission of the intelligent home wireless network is completed. The method has the advantages of good adaptivity and stability, high network security connectivity, strong survivability, high image compression efficiency, high transmission speed, capability of preventing personal privacy leakage, saving energy of sensor nodes, capability of watching and operating all monitoring pictures in a home at the first time and guarantee of personal and property safety.

Claims (3)

1. An intelligent household wireless network image encryption transmission optimization method is characterized by comprising the following steps: ensuring the communication safety by establishing a pairing key between the nodes;
the method comprises the following steps:
establishing an intelligent home wireless network topology model, acquiring a monitoring video image, and preprocessing the image;
performing discrete cosine transform on the processed image, quantizing the coefficient of the processed image, and performing image coding by searching the code word with the minimum distance;
the method comprises the steps that an n-dimensional hypercube is used for coding nodes of the intelligent home wireless network, a bivariate polynomial is selected as a secret key to be distributed to each node, and safe transmission is guaranteed through a matched secret key;
and constructing an optimal path for image transmission through the n-dimensional hypercube to complete encryption transmission optimization of the intelligent home wireless network image.
2. The intelligent home wireless network image encryption transmission optimization method according to claim 1, characterized in that: the step B comprises the following steps: if the codebook is full, finding the code word with the least using frequency number and not used in the current frame, and replacing the code word with the current vector.
3. The intelligent home wireless network image encryption transmission optimization method according to claim 1, characterized in that: the step C comprises the following steps: if there is no shared polynomial between node a and node B, a secret path negotiation key may be established.
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Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101414952A (en) * 2008-11-28 2009-04-22 西安邮电学院 Expandable parallel calculation interconnection network topological structure based on hypercube
CN101729899A (en) * 2009-11-02 2010-06-09 北京中星微电子有限公司 Method and device for encoding discrete cosine transform coefficient
CN102098161A (en) * 2009-12-15 2011-06-15 索尼公司 Actor node, sensor node, coverage block change method, parameter change method and information processing system
US20110150327A1 (en) * 2009-12-18 2011-06-23 Electronics And Telecommunications Research Institute Method and apparatus for masking privacy area of image
CN103188486A (en) * 2011-12-28 2013-07-03 联芯科技有限公司 Variable-length encoding method and system for H.263 video encoding
CN103987034A (en) * 2014-04-30 2014-08-13 南京邮电大学 Privacy protection method of soldier information in field battle environment
CN106059774A (en) * 2016-05-31 2016-10-26 东南大学 Data slice mixture privacy protection method based on cluster
US20170257225A1 (en) * 2016-03-07 2017-09-07 Luxul Technology Incorporation Smart switch controlling system and method thereof
CN107809761A (en) * 2017-11-23 2018-03-16 上海斐讯数据通信技术有限公司 A kind of wireless network connecting method and system based on intelligent home device
CN108737433A (en) * 2018-05-29 2018-11-02 冼汉生 Sensor node monitoring system based on Internet of Things and sensor node monitoring method
CN109068325A (en) * 2018-10-29 2018-12-21 南京邮电大学 A kind of key management and identity identifying method based on wireless sensor network
CN109165188A (en) * 2018-08-01 2019-01-08 苏州大学张家港工业技术研究院 Extend the parallel transmission method of data on cube structure multiprocessor network
WO2019091591A1 (en) * 2017-11-10 2019-05-16 Telefonaktiebolaget Lm Ericsson (Publ) Multipath policy decisions for encrypted video streams
US20190215180A1 (en) * 2016-03-25 2019-07-11 Afero, Inc. Internet of things (iot) apparatuses, systems and methods

Patent Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101414952A (en) * 2008-11-28 2009-04-22 西安邮电学院 Expandable parallel calculation interconnection network topological structure based on hypercube
CN101729899A (en) * 2009-11-02 2010-06-09 北京中星微电子有限公司 Method and device for encoding discrete cosine transform coefficient
CN102098161A (en) * 2009-12-15 2011-06-15 索尼公司 Actor node, sensor node, coverage block change method, parameter change method and information processing system
US20110150327A1 (en) * 2009-12-18 2011-06-23 Electronics And Telecommunications Research Institute Method and apparatus for masking privacy area of image
CN103188486A (en) * 2011-12-28 2013-07-03 联芯科技有限公司 Variable-length encoding method and system for H.263 video encoding
CN103987034A (en) * 2014-04-30 2014-08-13 南京邮电大学 Privacy protection method of soldier information in field battle environment
US20170257225A1 (en) * 2016-03-07 2017-09-07 Luxul Technology Incorporation Smart switch controlling system and method thereof
US20190215180A1 (en) * 2016-03-25 2019-07-11 Afero, Inc. Internet of things (iot) apparatuses, systems and methods
CN106059774A (en) * 2016-05-31 2016-10-26 东南大学 Data slice mixture privacy protection method based on cluster
WO2019091591A1 (en) * 2017-11-10 2019-05-16 Telefonaktiebolaget Lm Ericsson (Publ) Multipath policy decisions for encrypted video streams
CN107809761A (en) * 2017-11-23 2018-03-16 上海斐讯数据通信技术有限公司 A kind of wireless network connecting method and system based on intelligent home device
CN108737433A (en) * 2018-05-29 2018-11-02 冼汉生 Sensor node monitoring system based on Internet of Things and sensor node monitoring method
CN109165188A (en) * 2018-08-01 2019-01-08 苏州大学张家港工业技术研究院 Extend the parallel transmission method of data on cube structure multiprocessor network
CN109068325A (en) * 2018-10-29 2018-12-21 南京邮电大学 A kind of key management and identity identifying method based on wireless sensor network

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
李笑笑: "两跳中继分布式预编码码字选择方案", 《通信技术》 *
陈荷花: "基于超立方体Qn节点编码的最短路径", 《宜宾学院学报》 *
陈荷花: "基于超立方体Qn节点编码的边不交最优路径", 《太远师范学院学报》 *
陈荷花: "超立方体中过k个指定点的最短路径", 《山西师范大学学报》 *

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