CN108092826B - Wireless sensor network security model based on backbone node security role hierarchy - Google Patents

Wireless sensor network security model based on backbone node security role hierarchy Download PDF

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CN108092826B
CN108092826B CN201810044601.0A CN201810044601A CN108092826B CN 108092826 B CN108092826 B CN 108092826B CN 201810044601 A CN201810044601 A CN 201810044601A CN 108092826 B CN108092826 B CN 108092826B
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CN108092826A (en
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魏琴芳
袁岳义
胡向东
韩恺敏
白银
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Chongqing University of Post and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/04—Network management architectures or arrangements
    • H04L41/044—Network management architectures or arrangements comprising hierarchical management structures
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/20—Network architectures or network communication protocols for network security for managing network security; network security policies in general
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/04—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources
    • H04W40/10—Communication route or path selection, e.g. power-based or shortest path routing based on wireless node resources based on available power or energy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
    • 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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Abstract

The invention provides a backbone node security role hierarchy-based wireless sensor network security model, and belongs to the technical field of wireless sensor network security. The method comprises the steps that management nodes distributed by an dominating set principle divide wireless sensor network nodes deployed in a large scale into a plurality of local area subnets, and then the subnets are subdivided into clusters; the hierarchical backbone node composed of the sink node, the subnet management node and the cluster head is responsible for safety management and network maintenance, monitors the behavior of the managed node and evaluates and maintains the credit; the selection of the management node is weighted based on factors such as credit value and residual energy. The invention not only can improve the security of the wireless sensor network, but also has the characteristic of reducing the energy consumption of the network.

Description

Wireless sensor network security model based on backbone node security role hierarchy
Technical Field
The invention belongs to the technical field of wireless sensor network security, and relates to a wireless sensor network security model based on backbone node security role hierarchy.
Background
The innovative application of the internet and the innovative application of the internet of things are promoting the rapid expansion of wireless sensor networks to a plurality of application fields such as environment monitoring, disaster early warning, industrial control, security defense, smart home and intelligent traffic. Wireless sensor networks are typically deployed in unattended outdoor areas or even remote areas, and face a number of challenges. If the sensor nodes in the network are powered by batteries, the energy of the sensor nodes is limited and difficult to supplement, and the energy consumption of the nodes is high due to the frequent election of the cluster head nodes in the whole network; the network node has a simple structure and is easy to be captured by an attacker, so that data leakage is caused; an attacker can easily steal or forge data, control the nodes with legal identities to refuse service, replay attack, inject a large amount of redundant data and the like, and the network security faces severe examination and also puts forward new requirements on researchers. Therefore, how to design a low-power-consumption safety maintenance scheme under the condition that the resources of the wireless sensor network are limited is of great significance.
In the field of wireless sensor network security, researchers have proposed technologies and theories including identity authentication, key management and the like, but the traditional security method combined with the clustering mode of the wireless sensor network can face new challenges of large node energy consumption, short network life cycle and the like. Meanwhile, the problems of weak pertinence, single safety maintenance mode and the like exist in the aspect of safety. As a self-organizing network, the wireless sensor network has different node functions and different safety requirements of different types of nodes.
Disclosure of Invention
In view of this, the present invention provides a wireless sensor network security model based on backbone node security role hierarchy, so as to provide a wireless sensor network security role hierarchy model with high node energy efficiency, high malicious node detection rate, and high detection rate.
In order to achieve the purpose, the invention provides the following technical scheme:
the wireless sensor network security model based on the backbone node security role hierarchy specifically comprises the following steps:
s1: selecting management nodes by adopting a minimum dominating set algorithm, fusing the credit values of the nodes in the network and managing the distance between the nodes and the residual energy information by the management nodes, and maintaining the network safety;
s2: dividing the whole network into different subnets by taking a management node as a center, subdividing the subnets into clusters, selecting common nodes to add into the nearest cluster, and finally forming a security role hierarchical node structure consisting of a sink node, the management node, a cluster head node and the common nodes;
s3: counting the communication behaviors of adjacent nodes, calculating the credit values of the adjacent nodes by using a Bayes evaluation method according to the times of normal and abnormal communication behaviors of the nodes, and uploading the credit values to a management node;
s4: the node reputation value is stored and updated by the management node, and after the management node is rotated, the reputation value stored by the management node is uploaded to a new management node as a historical reputation value for management and storage;
s5: respectively calculating the current reputation value and the historical reputation value into new reputation values according to different weights, and quitting the backbone node election if the node reputation value is lower than a safety threshold R _ threshold;
s6: node residual energy ERDistance d between nodesijAnd a node reputation value RiIntroducing a communication weight W as a factor influencing the election of the management node; when the residual energy E of the nodeRThe larger the reputation value is, the higher the communication weight value is, and the lower the communication weight value of the node with the longer distance is;
if node viAnd vjThe sum of the communication weights satisfies;
(Wi+Wj)>W_manage
wherein W _ management represents the elected communication weight of the management node, WiAnd WjAre respectively node viAnd vjI, j equals to 1,2,3, …, n, the number of all nodes in the area subnet where the current node is located, v is theniAnd vjCan be connected, and the management node set V is reselected according to the minimum dominating set algorithmmanage；
S7: the condition is judged according to the number of the detected signals,
ER_manage>0.618ER_average
wherein E isR_manageIndicating the remaining energy of the management node, ER_averageRepresenting the average residual energy of the nodes in the sub-network;
if yes, executing step S5, otherwise executing step S6;
judging whether the reputation value of the management node is lower than a reputation threshold value R _ threshold, if so, executing a step S6;
judging whether the reputation value of the common node is lower than a reputation threshold value R _ threshold, if so, removing the common node from the network;
further, in step S1, the minimum dominating set algorithm is used to set the effective communication weight W _ message of the election management node based on the distance between the election management nodes in the whole network to determine whether the nodes can be connected, if yes,
(Wi+Wj)>W_manage
wherein, WiAnd WjAre respectively node viAnd vjCommunication weight, node viAnd vjCan be communicated;
in the initial stage, because the residual energy of each node is the same, the reputation value is the same according to the distance d between the nodesijAnd electing an assignment set node and giving up a management node.
Further, in step S3, the neighboring node reputation value is calculated by using Bayes evaluation method as:
Figure BDA0001550500880000021
Figure BDA0001550500880000022
Figure BDA0001550500880000031
wherein R isijIs v isjFor viThe reputation value of (d) is evaluated as r + f being a node viAnd vjThe current number of mutual communication, R is the number of normal communication, f is the number of abnormal communication, P (R)ijL R +1, f) is RijProbability of distribution of reputation values, E (R)ij) Is P (R)ijThe mathematical expectation of r +1, f),
Figure BDA0001550500880000032
is E (R)ij) Is determined by the average value of (a) of (b),
Figure BDA0001550500880000033
is the current reputation evaluation value.
Further, in step S5, the node reputation value is calculated and updated by using the current reputation evaluation and the historical reputation value weighting method,
Figure BDA0001550500880000034
wherein R isiFor the value of the node reputation to be,
Figure BDA0001550500880000035
for the purpose of the current reputation evaluation,
Figure BDA0001550500880000036
is a historical reputation value, mu is an adjustment factor, mu belongs to [0,1 ]]。
Further, in step S6, the calculation formula of the communication weight W is:
Figure BDA0001550500880000037
where α and β are weight adjustment factors, α + β is 1, E is a node initial energy value, R is an initial reputation value, and d is a boundary distance of the network.
Further, the reputation threshold R _ threshold is 0.2.
The invention has the beneficial effects that: the invention firstly divides the subnets based on the dominating set in the whole network, and reduces the energy over consumption caused by large-range communication in the process of cluster head rotation by a method of selecting the cluster heads in the subnets. And selecting the management nodes of the sub-network while dividing the sub-network, wherein the management nodes are responsible for the safety supervision work of the cluster head nodes and the common nodes in the sub-network. The invention adopts a dividing method of hierarchical roles of backbone nodes, thereby defining the safe communication range of the nodes and avoiding partial malicious node attacks. Meanwhile, a credit evaluation mechanism is added, and the nodes with higher credit values are selected to serve as backbone nodes, so that the safety of the data fusion stage is improved. Therefore, the method and the device can effectively find and remove the malicious nodes, improve the network security, reduce the node energy consumption and prolong the network life cycle.
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In order to make the object, technical scheme and beneficial effect of the invention more clear, the invention provides the following drawings for explanation:
FIG. 1 is a flow chart of the present invention based on a hierarchical scheme of security roles for backbone nodes;
FIG. 2 is a security role hierarchy network topology of the present invention;
FIG. 3 is a schematic diagram of a node reputation value algorithm of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.
Referring to a flow chart of a security clustering algorithm shown in fig. 1, a wireless sensor network security model based on a backbone node security role hierarchy includes the following steps:
101: and (4) selecting management nodes in the whole network based on the distance by using a minimum dominating set algorithm. Setting the election communication weight W _ message of the election management node to determine whether the node can be connected, if (W)i+Wj)>W _ management is node viAnd vjCan be communicated. In the initial stage, because the residual energy of each node is the same, the network will be according to the distance d between nodesijAnd electing an assignment set node and giving up a management node.
102, taking a management node as a center, dividing the whole network into different subnets, subdividing the subnets into clusters, selecting and adding a common node into the nearest cluster, and finally forming a security role hierarchical node structure consisting of a sink node, the management node, a cluster head node and the common node; the sink node is a data sink center of the whole network and exchanges information with an external network through the sink node, and the whole network only has one sink node; the cluster head node is a unique management node of each cluster, is responsible for managing common nodes in the cluster and collecting and processing data, and transmits a processing result to the sink node; the common node is a node except for the cluster head node in a cluster and is mainly responsible for collecting data and transmitting the data to the cluster head node. In the invention, the nodes select cluster head nodes in each sub-network, and the nodes among different sub-networks cannot select each other.
103, evaluating the current reputation of the node. And (4) counting the communication behaviors of the adjacent nodes, calculating the credit values of the adjacent nodes by using a Bayes evaluation method according to the times of normal and abnormal communication behaviors of the nodes, and uploading the credit values to the management node.
104 node historical reputation values. And after the management nodes are rotated, the stored reputation value is uploaded to a new management node as a historical reputation value to be managed and stored.
And (5) updating the reputation value of the node. And respectively calculating the current reputation value and the historical reputation value into new reputation values according to different weights, and if the node reputation value is lower than a reputation threshold value R _ threshold, exiting the network.
106 manage node rotation. Node residual energy ERDistance d between nodesijAnd a node reputation value RiThe communication weight W is introduced as a factor affecting the election of the management node. When the node residual energy is more, the reputation value is higher, the communication weight value is higher, and the communication weight value is lower when the distance is farther. If node viAnd vjIf the sum of the communication weights of (1) is greater than W _ management, v isiAnd vjCan be connected, and the management node set V is reselected according to the minimum dominating set algorithmmanage；
107, judging whether the residual energy of the management node is larger than 0.618 times of the average residual energy of the nodes in the subnet, if so, skipping to S5, and if not, skipping to S6; judging whether the reputation value of the management node is lower than a reputation threshold value R _ threshold (the threshold value is set to be 0.2), and jumping to S6 if the reputation value of the management node is lower than the reputation threshold value; judging whether the reputation value of the common node is lower than a reputation threshold value R _ threshold, and if the reputation value of the common node is lower than the reputation threshold value, quitting the network;
in steps 101, 102 the subnetworks are divided based on the minimum dominance set
A. In the invention, the wireless sensing network node is represented by an undirected graph, and G is<V,E>Where V is the set of all sensor nodes, V ═ V1,v2…vn}; e is the link set for all sensor nodes, E ═ E (v)i,vj)}；e(vi,vj) Is a sensor node vi，vjCommunication link between vi，vjAre adjacent communication nodes.
B. As shown in fig. 2, the management node is used as a center, the whole network is divided into a plurality of subnets, the subnets are subdivided into clusters, the common nodes are selected to join the nearest cluster, and the cluster head is responsible for fusing monitoring data acquired by the common nodes and uploading the monitoring data to the base station. And the management node is responsible for fusing information such as the reputation value, the residual energy and the like of the common nodes in the subnet.
In calculating the node reputation values in steps 103,104, 105, as shown in figure 3,
A. node v is solved by Bayes evaluation methodjFor viThe credit value is converted into posterior probability through a Bayes formula by utilizing a known conditional probability density parameter expression and prior probability, and decision classification is carried out according to the posterior probability. Suppose node viAnd vjThe current mutual communication is r + f times, wherein the normal communication is r times, the abnormal communication is f times, and the credit value of the abnormal communication is punished, so the v can be obtained by a Bayesian evaluation methodjFor viStatistical reputation ofijHas a distribution probability of
Figure BDA0001550500880000051
Figure BDA0001550500880000052
Calculating the average value
Figure BDA0001550500880000053
I.e. node viCurrent reputation value of
Figure BDA0001550500880000054
Wherein i, j is 1,2,3 … n. n is the current node viThe number of all nodes in the subnet of the area.
B. When the management node enters new election after a period, the regional sub-network in the network is divided again, each node of the divided sub-network has a certain number of new nodes to give credit values, and the credit value of the current node is used as a historical credit value
Figure BDA0001550500880000055
And the node reputation value is included in the calculation.
C. And calculating and updating the node reputation value by adopting a current reputation evaluation and historical reputation value weighting mode. Which is represented by
Figure BDA0001550500880000056
Wherein the content of the first and second substances,
Figure BDA0001550500880000057
for the purpose of the current reputation evaluation,
Figure BDA0001550500880000058
is a historical credit value, mu is an adjustment factor, and the value range of mu is [0, 1%]。
In the step 106, the invention calculates the node residual energy E in the communication weight calculation of the nodeRDistance d between nodesijAnd a node reputation value RiAs a factor affecting the election of the management node. Introducing a communication weight W, wherein when the residual energy of the nodes is more, the credit value is higher, the communication weight is higher, and the communication weight is lower when the distance is longer; influencing factors alpha and beta are added as regulating factors.
Figure BDA0001550500880000059
Where α + β is 1, normalization processing is performed on different variables in the above formula, where E is an initial energy value of a node, R is an initial reputation value, and d is a boundary distance.
The method is suitable for constructing the security model aiming at the wireless sensor network, and management nodes are elected in the wireless sensor network based on the minimum domination set algorithm by using the security model disclosed by the invention. The management nodes are used for dividing the subnets, the communication range in the node information fusion process is reduced, meanwhile, a credit evaluation mechanism is introduced to screen malicious nodes, the effects of high detection accuracy, high detection speed and network energy consumption saving are achieved, and the purpose of improving the network performance is achieved.
Finally, it is noted that the above-mentioned preferred embodiments illustrate rather than limit the invention, and that, although the invention has been described in detail with reference to the above-mentioned preferred embodiments, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the scope of the invention as defined by the appended claims.

Claims (6)

1. The wireless sensor network security model based on the backbone node security role hierarchy is characterized in that: the method specifically comprises the following steps:
s1: selecting management nodes by adopting a minimum dominating set algorithm, fusing the credit values of the nodes in the network and managing the distance between the nodes and the residual energy information by the management nodes, and maintaining the network safety;
s2: dividing the whole network into different subnets by taking a management node as a center, subdividing the subnets into clusters, selecting common nodes to add into the nearest cluster, and finally forming a security role hierarchical node structure consisting of a sink node, the management node, a cluster head node and the common nodes;
s3: counting the communication behaviors of adjacent nodes, calculating the credit values of the adjacent nodes by using a Bayes evaluation method according to the times of normal and abnormal communication behaviors of the nodes, and uploading the credit values to a management node;
s4: the node reputation value is stored and updated by the management node, and after the management node is rotated, the reputation value stored by the management node is uploaded to a new management node as a historical reputation value for management and storage;
s5: the current credit value and the historical credit value are respectively calculated into new credit values according to different weights, if the node credit value is lower than the credit threshold value
Figure DEST_PATH_IMAGE002
If yes, exiting the network;
s6: remaining energy of node
Figure DEST_PATH_IMAGE004
Distance between nodes
Figure DEST_PATH_IMAGE006
And node reputation value
Figure DEST_PATH_IMAGE008
Introducing communication weight as a factor affecting election of management nodes
Figure DEST_PATH_IMAGE010
(ii) a Residual energy of current node
Figure 13359DEST_PATH_IMAGE004
The larger the reputation value is, the higher the communication weight value is, and the lower the communication weight value of the node with the longer distance is;
if node
Figure DEST_PATH_IMAGE012
And
Figure DEST_PATH_IMAGE014
the sum of the communication weights satisfies;
Figure DEST_PATH_IMAGE016
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE018
the election communication weight of the management node is shown,
Figure DEST_PATH_IMAGE020
are respectively nodes
Figure 235174DEST_PATH_IMAGE012
And
Figure 692700DEST_PATH_IMAGE014
the communication weight of (a) is set,
Figure DEST_PATH_IMAGE022
，
Figure DEST_PATH_IMAGE024
the number of all nodes in the subnet of the area where the current node is located is determined
Figure 195487DEST_PATH_IMAGE012
And
Figure 80267DEST_PATH_IMAGE014
can be connected, and the management node set can be reselected according to the minimum dominating set algorithm
Figure DEST_PATH_IMAGE026
；
S7: the condition is judged according to the number of the detected signals,
Figure DEST_PATH_IMAGE028
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE030
indicating the remaining energy of the management node,
Figure DEST_PATH_IMAGE032
representing the average residual energy of the nodes in the sub-network;
if yes, executing step S5, otherwise executing step S6;
judging whether the credit value of the management node is lower than the credit threshold value
Figure 721201DEST_PATH_IMAGE002
If yes, go to step S6;
judging whether the credit value of the common node is lower than the credit threshold value
Figure 982419DEST_PATH_IMAGE002
And if so, removing the common node from the network.
2. The backbone node security role hierarchy-based wireless sensor network security model of claim 1, wherein: in step S1, the effective communication weight of the election management node is set based on the distance in the whole network election management node by using the minimum dominating set algorithm
Figure DEST_PATH_IMAGE034
To ascertain whether the nodes can communicate and, if so,
Figure DEST_PATH_IMAGE016A
wherein the content of the first and second substances,
Figure 416678DEST_PATH_IMAGE020
are respectively nodes
Figure 472359DEST_PATH_IMAGE012
And
Figure 790470DEST_PATH_IMAGE014
communication weight, node
Figure 589799DEST_PATH_IMAGE012
And
Figure 175501DEST_PATH_IMAGE014
can be communicated;
in the initial stage, because the residual energy of each node is the same, the reputation value is the same according to the distance between the nodes
Figure 667662DEST_PATH_IMAGE006
And electing an assignment set node and giving up a management node.
3. The backbone node security role hierarchy-based wireless sensor network security model of claim 2, wherein: in step S3, the Bayes evaluation method is used to calculate the reputation value of the neighboring node as:
Figure DEST_PATH_IMAGE036
Figure DEST_PATH_IMAGE038
Figure DEST_PATH_IMAGE040
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE042
is composed of
Figure 407823DEST_PATH_IMAGE014
To pair
Figure 249658DEST_PATH_IMAGE012
The reputation value of (a) is evaluated,
Figure DEST_PATH_IMAGE044
is a node
Figure 17762DEST_PATH_IMAGE012
And
Figure 415246DEST_PATH_IMAGE014
the number of times of current mutual communication,
Figure DEST_PATH_IMAGE046
in order to have a normal number of communications,
Figure DEST_PATH_IMAGE048
in order to determine the number of abnormal communications,
Figure DEST_PATH_IMAGE050
is composed of
Figure 894900DEST_PATH_IMAGE042
The probability of the distribution of the reputation value,
Figure DEST_PATH_IMAGE052
and
Figure DEST_PATH_IMAGE054
all represent density function
Figure DEST_PATH_IMAGE056
Is composed of
Figure DEST_PATH_IMAGE057
The mathematical expectation of (a) is that,
Figure DEST_PATH_IMAGE059
is composed of
Figure 27242DEST_PATH_IMAGE056
Is determined by the average value of (a) of (b),
Figure DEST_PATH_IMAGE061
is the current reputation evaluation value.
4. The backbone node security role hierarchy-based wireless sensor network security model of claim 3, wherein: in step S5, the node reputation value is calculated and updated by using the current reputation evaluation and the historical reputation value weighting method,
Figure DEST_PATH_IMAGE063
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE064
for the value of the node reputation to be,
Figure 400586DEST_PATH_IMAGE061
for the purpose of the current reputation evaluation,
Figure DEST_PATH_IMAGE066
in order to be a value of the historical reputation,
Figure DEST_PATH_IMAGE068
in order to adjust the factors, the method comprises the following steps,
Figure DEST_PATH_IMAGE070
[0,1]。
5. the backbone node security role hierarchy-based wireless sensor network security model of claim 4, wherein: in the step S6, the communication weight
Figure DEST_PATH_IMAGE071
The calculation formula of (2) is as follows:
Figure DEST_PATH_IMAGE073
wherein the content of the first and second substances,
Figure DEST_PATH_IMAGE075
in order to adjust the weight of the factor,
Figure DEST_PATH_IMAGE077
，
Figure DEST_PATH_IMAGE079
in order to be the initial energy value of the node,
Figure DEST_PATH_IMAGE081
in the form of an initial reputation value, the reputation value,
Figure DEST_PATH_IMAGE083
is the boundary distance of the network.
6. The backbone node security role hierarchy-based wireless sensor network of claim 1A security model characterized by: the reputation threshold
Figure DEST_PATH_IMAGE084
Is 0.2.
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