CN111541494B - Location privacy protection method based on clustering structure in underwater acoustic sensor network - Google Patents

Location privacy protection method based on clustering structure in underwater acoustic sensor network Download PDF

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CN111541494B
CN111541494B CN202010541724.2A CN202010541724A CN111541494B CN 111541494 B CN111541494 B CN 111541494B CN 202010541724 A CN202010541724 A CN 202010541724A CN 111541494 B CN111541494 B CN 111541494B
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cluster head
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CN111541494A (en
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韩光洁
陈玉思
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Changzhou Campus of Hohai University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B13/00—Transmission systems characterised by the medium used for transmission, not provided for in groups H04B3/00 - H04B11/00
    • H04B13/02—Transmission systems in which the medium consists of the earth or a large mass of water thereon, e.g. earth telegraphy
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L45/00—Routing or path finding of packets in data switching networks
    • H04L45/46—Cluster building
    • 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
    • H04W12/02—Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/24—Connectivity information management, e.g. connectivity discovery or connectivity update
    • H04W40/32—Connectivity information management, e.g. connectivity discovery or connectivity update for defining a routing cluster membership
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract

The invention discloses a position privacy protection method based on a clustering structure in an underwater sound sensor network. And then the nodes are clustered, after the number and the positions of the cluster heads are determined, other nodes are added into corresponding clusters according to the principle of proximity, and then auxiliary cluster heads are selected according to the residual energy of the nodes and the positions of the nodes to the base station. And finally, data transmission is carried out, one part of auxiliary cluster heads carry out real data packet transmission, the other part of auxiliary cluster heads generate a false data packet and carry out false data packet transmission, then the data packet is transmitted to the base station through multi-hop transmission and AUV, the next hop is selected through a neighbor list in transmission between nodes, and the path planning of the AUV is realized based on Q-learning.

Description

Location privacy protection method based on clustering structure in underwater acoustic sensor network
Technical Field
The invention belongs to the field of privacy security in an underwater acoustic sensor network, and particularly relates to a location privacy protection method based on a clustering structure in the underwater acoustic sensor network.
Background
In the past decades, human demand for energy has increased rapidly with increasing population, and the oceans cover 71% of the earth's surface and are considered to be the current major source of human living resources. UASNs include underwater nodes deployed in a sensing area and underwater autonomous vehicles for collecting data packets. UASNs are widely applied, can be applied to aspects such as marine resource exploration, pollution detection, earthquake monitoring, military monitoring and the like, and are widely concerned in recent years. However, since UASNs are generally deployed in inaccessible, unattended, and even contradictory situations, deployed underwater nodes are relatively vulnerable to damage and attack, and face serious security problems. Therefore, a relatively secure and private environment is necessary for the normal operation of UASNs, and the present disclosure is of some research interest.
Privacy threats can be generally classified as: content privacy and contextual privacy. The content privacy threat means that an attacker acquires the data content and the identification and the position of a source node by monitoring the content of a data packet sent in a network. To address this privacy threat, data packets are typically encrypted and pseudonyms are used instead of true identities, and contextual privacy threats refer to attacks that eavesdrop on network transmissions and use traffic analysis techniques to infer sensitive information, i.e., when and where to collect data.
The underwater acoustic sensor network generally comprises underwater sensor nodes, sink nodes, sea surface base stations, data centers and the like. The underwater sensor nodes are thrown in an underwater area to be detected, and are usually deployed in the sea with different distances relative to the sea surface in order to more comprehensively acquire some parameters in the sea. When the underwater acoustic sensor network operates, the sensor nodes firstly sense a sensing area and transmit sensed data to the sink nodes in a multi-hop transmission or AUV (autonomous Underwater vehicle) transmission mode, the sink nodes perform data fusion and then transmit data packets to the sea surface base station in the same mode, and the sea surface base station transmits the data packets to the data center in a wireless communication mode to process the data. In the process, if an attacker acquires the position of the data transmission node according to the tracking data or other modes so as to acquire the position of an important underwater node or important equipment, the underwater acoustic sensor network is threatened greatly. The position privacy protection in the underwater acoustic sensor network can be aimed at important nodes, sea surface base stations and the like, and the position privacy protection for source nodes is mainly researched herein.
At present, many methods such as phantom routing, dummy packet injection, random routing and the like are available for protecting the source node position privacy of the wireless sensor network. Based on source node privacy protection for WSNs, the method is applied to UASNs for protecting source node location privacy in UASNs. However, the application process of UASNs, which are unique features such as three-dimensional environment, high propagation delay, limited bandwidth, path loss, mobility, etc., is relatively more troublesome, and is mainly shown in these three points:
1) the energy, computing power and storage space of the underwater sensor node are limited;
2) UASNs adopt acoustic communication, and the transmission rate is limited;
3) the complexity of the underwater environment.
The objective of the study herein is to protect the various complex devices on which UASNs live, once captured, the entire network of underwater acoustic sensors will be at risk and thus critical to the protection of the various complex devices underwater.
Disclosure of Invention
Aiming at the problems, the invention provides a position privacy protection method based on a clustering structure in an underwater acoustic sensor network, which is characterized in that the underwater acoustic sensor network is divided by utilizing ocean characteristics, and the difficulty of capturing source nodes by an attacker is increased through node clustering, the calling of cluster heads, the multi-hop transmission of data packets and the operation of AUV (autonomous Underwater vehicle), so that the safety time of the network is prolonged, and the position privacy protection effect is achieved.
A location privacy protection method based on a clustering structure in an underwater acoustic sensor network comprises the following steps:
(1) network division, namely dividing the underwater acoustic sensor network into a static layer and a dynamic layer, wherein each layer is provided with an AUV (autonomous Underwater vehicle) for data transmission;
(2) the nodes are clustered, after the number and the positions of cluster heads are determined, other nodes are added into corresponding clusters according to the principle of proximity, and then auxiliary cluster heads are selected according to the residual energy of the nodes and the positions of the nodes to the base station;
(3) and data transmission, wherein one part of the auxiliary cluster heads transmit real data packets, the other part of the auxiliary cluster heads generate false data packets and transmit the false data packets, then the data packets are transmitted to the base station through multi-hop transmission and AUV (autonomous Underwater vehicle), the next hop is selected through a neighbor list in the transmission between nodes, and the path planning of the AUV is realized based on Q-learning.
The specific steps of the step (1) are as follows:
firstly, dividing the underwater acoustic sensor network into a static layer and a dynamic layer. Setting an area 200m away from the ocean surface as a dynamic layer, and setting an area more than 200m away from the ocean surface as a static layer; the important equipment is anchored on the seabed of a static layer, sensor nodes of the static layer are clustered at first, a main cluster head and an auxiliary cluster head are selected, data collected by common sensor nodes are upwards transmitted to a dynamic layer by means of the main cluster head and the auxiliary cluster head, and then the data are routed to a base station.
The specific steps of the step (2) are as follows:
(2.1) determining the number and location of cluster heads
First, the number of cluster heads is determined. Since the number of cluster heads determines the final number of clusters. If the cluster heads are too many, clusters are more, the similarity between the clusters is too high, effective data fusion cannot be executed, and the clustering purpose cannot be achieved. If the cluster head is too few, the cluster is relatively few, which means that the cluster range is too large and the number of nodes is too many, and the long distance transmission of the nodes when the cluster head collects data will result in increased energy consumption.
Assuming that the number of initial cluster heads in UASNs is C, the total number of sensor nodes is M, and the average number of sensor nodes in each cluster is M/C; if the network size is L × L × L, the calculation formula of the optimal initial cluster head number is as follows:
Figure BDA0002539115820000031
dE(toBS)is the expected value of the node-to-base station distance;
then, the position of the cluster head needs to be determined. If the cluster heads are randomly located, it may happen that the cluster heads are piled up or at the edge of the network, which may lead to a situation of local optimality or cluster instability.
Based on LEACH protocol, a sensor node randomly generates a random number x, wherein x belongs to [0,1], if x is smaller than a corresponding threshold Th, the node is elected to be a cluster head, and the calculation formula of Th is as follows:
Figure BDA0002539115820000032
p is the probability of the node to select the cluster head, r is the current round number, ρ is the density of the sensor node (which can be defined as the ratio of the number of nodes in the communication range to the total number of nodes), D is the node depth, D is the total number of nodesmaxIs the distance between the bottommost node and the topmost node;
(2.2) clustering
After the positions of the C cluster heads are determined, other common sensor nodes enter corresponding clusters according to the principle of proximity, each common sensor node calculates the Euclidean distance from the common sensor node to the selected cluster head according to the following formula (3), and then the cluster head with the minimum Euclidean distance is added; the calculation formula of the euclidean distance is as follows:
E＝dist(C,x)2 (3)
c represents a cluster head, and x represents a common sensor node in the cluster;
(2.3) selecting an auxiliary Cluster head
After the number and the positions of the cluster heads are determined, each cluster head in the cluster serves as a main cluster head of the cluster; the task of the main cluster head is to collect sensed data of common sensor nodes in the cluster, then perform data fusion and data fragmentation, and then send the fragmented data to the auxiliary cluster head;
the auxiliary cluster heads are divided into two types, one type is the auxiliary cluster head which receives the data sent by the main cluster head and transmits the received data to the base station upwards; the other is an auxiliary cluster head which does not receive the data sent by the main cluster head, a false data packet is generated and is upwards transmitted to the base station together with real data packets of other auxiliary cluster heads;
the selection of the auxiliary cluster head is selected according to the residual energy of the node and the distance between the node and the base station, the influence factor of the auxiliary cluster head is A, the larger the value of A is, the higher the probability of being selected as the auxiliary cluster head is, and the calculation formula of A is as follows:
Figure BDA0002539115820000041
Eleftis the residual energy of the node, b is a constant, dtoBSIs the node-to-base station distance.
The specific steps of the step (3) are as follows:
(3.1) Intra-Cluster data transfer
After the main cluster head and the auxiliary cluster heads are determined, other nodes in the cluster send sensed data to the main cluster head, the main cluster head performs data fusion, data fragmentation is performed after the data fusion of the main cluster head is completed, then the data are transmitted to a plurality of randomly selected auxiliary cluster heads, and the auxiliary cluster heads transmit upwards; generating false data packets by the rest auxiliary cluster heads and sending the false data packets upwards;
(3.2) data transfer at the interface between static and dynamic layers
1) If the auxiliary cluster head cannot sense the AUV of the dynamic layer within the communication range, the auxiliary cluster head transmits the data packet to the nearest node of the dynamic layer, and if the nearest node of the dynamic layer cannot sense the AUV of the dynamic layer within the time t (self-setting), the auxiliary cluster head directly transmits the data packet to the base station;
2) if the auxiliary cluster head does not sense the AUV of the static layer in the communication range of the auxiliary cluster head, the auxiliary cluster head transmits a data packet to the nearest node of the dynamic layer, and if the nearest node of the dynamic layer senses the AUV of the dynamic layer within the time t (autonomous setting), the AUV of the dynamic layer floats to the base station to transmit the data packet to the base station;
3) the auxiliary cluster head senses a static layer AUV in a communication range of the auxiliary cluster head, the auxiliary cluster head sends a data packet to the static layer AUV, the static layer AUV floats to a junction of the static layer and a dynamic layer, the data packet is sent to the dynamic layer AUV, and the dynamic layer AUV floats to a base station to send the data packet to the base station;
(3.3) Multi-hop data Transmission
If the node of the dynamic layer can not sense the AUV of the dynamic layer in the communication range within the time t, the node directly transmits a data packet to a base station, and the process is realized by utilizing a neighbor list of the node; each node is provided with a neighbor list which is updated regularly, and the stored content of the neighbor list is the hop number of the node and the neighbor nodes to reach the base station;
when a next hop is selected in the process of transmitting a data packet to the base station by the node, selecting any node which is smaller than or equal to the hop count of the node from the base station in the neighbor list until the node which has only one hop away from the base station is transmitted, and directly transmitting the data packet to the base station by the node;
(3.4) AUV data transfer
The path of the AUV is planned based on Q-learning, and the AUV walks in the underwater acoustic sensor network according to the planned path by establishing an environment state model, a behavior action model, a reward function model and the like.
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FIG. 1 is a schematic diagram of a network model according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of data transmission at the interface between the static layer and the dynamic layer according to the present invention;
FIG. 3 is a schematic diagram of data transmission between nodes according to the present invention;
fig. 4 is a neighbor list of a node of the present invention.
Detailed Description
The invention divides the underwater acoustic sensor network into a static layer and a dynamic layer, and each layer is provided with an AUV for data transmission. And then, after the number and the positions of the cluster heads are determined through a calculation formula, other nodes are added into corresponding clusters according to a proximity principle, and then auxiliary cluster heads are selected according to the residual energy of the nodes and the positions of the nodes to the base station. And finally, data transmission is carried out, one part of auxiliary cluster heads carry out real data packet transmission, the other part of auxiliary cluster heads generate a false data packet and carry out false data packet transmission, then the data packet is transmitted to the base station through multi-hop transmission and AUV, the next hop is selected through a neighbor list in transmission between nodes, and the path planning of the AUV is realized based on Q-learning. According to the invention, the difficulty of capturing the source node by an attacker is increased through node clustering, auxiliary cluster head calling, multi-hop transmission of a data packet and AUV operation, so that the position privacy protection effect is achieved.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The following detailed description of the principles of the invention is provided in connection with the accompanying drawings.
Fig. 1 is a schematic diagram of an underwater acoustic sensor network model, where the sensor network is a three-dimensional underwater acoustic sensor network, and the whole network is divided into a static layer and a dynamic layer; assuming that all nodes (including a main cluster head node, an auxiliary cluster head node and a relay node) have independent IDs and have the same initial energy, transmission range, computing capacity and storage capacity in the initial condition; all nodes of the static layer are assumed to be static, the positions of the nodes are not changed, and the nodes are uniformly distributed; in the invention, the cluster head collecting data in each cluster is regarded as a source node needing protection.
Step (1): dividing a network;
firstly, dividing the underwater acoustic sensor network into a static layer and a dynamic layer. The area 200m from the ocean surface is set as a dynamic layer, and the area more than 200m from the ocean surface is set as a static layer. The important equipment is anchored on the seabed of a static layer, sensor nodes of the static layer are clustered at first, a main cluster head and an auxiliary cluster head are selected, data collected by common sensor nodes are upwards transmitted to a dynamic layer by means of the main cluster head and the auxiliary cluster head, and then the data are routed to a base station.
Step (2): clustering nodes;
(2.1) determining the number and location of cluster heads
First, the number of cluster heads is determined. Since the number of cluster heads determines the final number of clusters. If the cluster heads are too many, clusters are more, the similarity between the clusters is too high, effective data fusion cannot be executed, and the clustering purpose cannot be achieved. If the cluster head is too few, the cluster is relatively few, which means that the cluster range is too large and the number of nodes is too many, and the long distance transmission of the nodes when the cluster head collects data will result in increased energy consumption.
Assuming that the number of initial cluster heads in UASNs is C, the total number of sensor nodes is M, and the average number of sensor nodes in each cluster is M/C; if the network size is L × L × L, the calculation formula of the optimal initial cluster head number is as follows:
Figure BDA0002539115820000061
dE(toBS)is the expected value of the node-to-base station distance;
then, the position of the cluster head is determined. If the cluster heads are randomly located, it may happen that the cluster heads are piled up or at the edge of the network, which may lead to a situation of local optimality or cluster instability.
Based on LEACH protocol, a sensor node randomly generates a random number x, wherein x belongs to [0,1], if x is smaller than a corresponding threshold Th, the node is elected to be a cluster head, and the calculation formula of Th is as follows:
Figure BDA0002539115820000071
p is the probability of the node selecting the cluster head, r is the current round number, which is the density of the sensor node (which can be defined as the ratio of the node number in the communication range to the total node number), D is the node depth, which is the distance between the node at the bottommost part and the node at the topmost part;
(2.2) clustering
After the positions of the C cluster heads are determined, other common sensor nodes enter corresponding clusters according to the principle of proximity, each common sensor node calculates the Euclidean distance from the common sensor node to the selected cluster head according to the following formula (3), and then the cluster head with the minimum Euclidean distance is added; the calculation formula of the euclidean distance is as follows:
E＝dist(C,x)2 (3)
c represents a cluster head, and x represents a common sensor node in the cluster;
(2.3) selecting an auxiliary Cluster head
After the number and the positions of the cluster heads are determined, each cluster head in the cluster serves as a main cluster head of the cluster; the task of the main cluster head is to collect sensed data of common sensor nodes in the cluster, then perform data fusion and data fragmentation, and then send the fragmented data to the auxiliary cluster head;
the auxiliary cluster heads are divided into two types, one type is the auxiliary cluster head which receives the data sent by the main cluster head and transmits the received data to the base station upwards; the other is an auxiliary cluster head which does not receive the data sent by the main cluster head, a false data packet is generated and is upwards transmitted to the base station together with real data packets of other auxiliary cluster heads;
the selection of the auxiliary cluster head is selected according to the residual energy of the node and the distance between the node and the base station, the influence factor of the auxiliary cluster head is A, the larger the value of A is, the higher the probability of being selected as the auxiliary cluster head is, and the calculation formula of A is as follows:
Figure BDA0002539115820000072
Eleftis the residual energy of the node, b is a constant, dtoBSIs the node-to-base station distance.
And (3): data transmission;
(3.1) Intra-Cluster data transfer
After the main cluster head and the auxiliary cluster heads are determined, other nodes in the cluster send sensed data to the main cluster head, the main cluster head performs data fusion, data fragmentation is performed after the data fusion of the main cluster head is completed, then the data are transmitted to a plurality of randomly selected auxiliary cluster heads, and the auxiliary cluster heads transmit upwards; generating false data packets by the rest auxiliary cluster heads and sending the false data packets upwards;
(3.2) data transfer at the interface between static and dynamic layers
Fig. 2 is a schematic diagram of three data transmission modes at the boundary between the static layer and the dynamic layer, which is specifically described as follows:
1) if the auxiliary cluster head cannot sense the AUV of the dynamic layer within the communication range, the auxiliary cluster head transmits the data packet to the nearest node of the dynamic layer, and if the nearest node of the dynamic layer cannot sense the AUV of the dynamic layer within the time t, the auxiliary cluster head directly transmits the data packet to the base station;
2) if the auxiliary cluster head does not sense the AUV of the static layer in the communication range of the auxiliary cluster head, the auxiliary cluster head transmits a data packet to the nearest node of the dynamic layer, and if the nearest node of the dynamic layer senses the AUV of the dynamic layer within the time t, the AUV of the dynamic layer floats to the base station to transmit the data packet to the base station;
3) the auxiliary cluster head senses a static layer AUV in a communication range of the auxiliary cluster head, the auxiliary cluster head sends a data packet to the static layer AUV, the static layer AUV floats to a junction of the static layer and a dynamic layer, the data packet is sent to the dynamic layer AUV, and the dynamic layer AUV floats to a base station to send the data packet to the base station;
(3.3) Multi-hop data Transmission
If the node of the dynamic layer can not sense the AUV of the dynamic layer in the communication range within the time t, the node directly transmits a data packet to a base station, and the process is realized by utilizing a neighbor list of the node; each node is provided with a neighbor list which is updated regularly, and the stored content of the neighbor list is the hop number of the node and the neighbor nodes to reach the base station;
when a next hop is selected in the process of transmitting a data packet to the base station by the node, selecting any node which is smaller than or equal to the hop count of the node from the base station in the neighbor list until the node which has only one hop away from the base station is transmitted, and directly transmitting the data packet to the base station by the node;
fig. 3 is a schematic diagram of data transmission between nodes, and for node 0 in fig. 3, its neighbor list is shown in fig. 4. Specifically, the node-to-base station hop count is 4, the node 2-to-base station hop count is greater than the node-to-base station hop count, the node 1 and node 3-to-base station hop counts are less than the node-to-base station hop count, and the node 4-to-base station hop count is equal to the node-to-base station hop count. Then the node will randomly select one node from among nodes 1, 3 and 4 having a smaller or the same number of hops to the base station as the next hop when selecting the next hop. And so on until the hop count from the next hop node to the base station is 1.
(3.4) AUV data transfer
The path of the AUV is planned based on Q-learning, and the AUV walks in the underwater acoustic sensor network according to the planned path by establishing an environment state model, a behavior action model, a reward function model and the like.
The foregoing illustrates and describes the principles, operation and advantages of the present invention. It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the technical spirit thereof, and these modifications and variations should be construed as the scope of the present invention.

Claims (3)

1. A location privacy protection method based on a clustering structure in an underwater acoustic sensor network is characterized in that: the method comprises the following steps:
(1) network partitioning
Dividing the underwater acoustic sensor network into a static layer and a dynamic layer, wherein each layer is provided with an AUV (autonomous Underwater vehicle) for data transmission;
(2) node clustering
After the number and the positions of the cluster heads are determined, other nodes are added into corresponding clusters according to the principle of proximity, and then auxiliary cluster heads are selected according to the residual energy of the nodes and the positions of the nodes to the base station;
(3) data transmission
One part of the auxiliary cluster heads transmits real data packets, the other part of the auxiliary cluster heads generates false data packets and transmits the false data packets, then the data packets are transmitted to a base station through multi-hop transmission and an AUV, the next hop is selected through a neighbor list in the transmission between nodes, and the path planning of the AUV is realized based on Q-learning;
the specific steps of the step (2) are as follows:
(2.1) determining the number and location of cluster heads
First, the number of cluster heads is determined
Assuming that the number of initial cluster heads in UASNs is C, the total number of sensor nodes is M, and the average number of sensor nodes in each cluster is M/C; if the network size is L × L × L, the calculation formula of the optimal initial cluster head number is as follows:
Figure FDA0003202578780000011
dE(toBS)is the expected value of the node-to-base station distance;
then, the position of the cluster head needs to be determined
Based on LEACH protocol, a sensor node randomly generates a random number x, wherein x belongs to [0,1], if x is smaller than a corresponding threshold Th, the node is elected to be a cluster head, and the calculation formula of Th is as follows:
Figure FDA0003202578780000012
p is the probability of the node selecting the cluster head; r is the current number of rounds; rho is the density of the sensor nodes and is defined as the ratio of the number of nodes in the communication range to the total number of nodes; d is the node depth, DmaxIs the distance between the bottommost node and the topmost node;
(2.2) clustering
After the positions of the C cluster heads are determined, other common sensor nodes enter corresponding clusters according to the principle of proximity, each common sensor node calculates the Euclidean distance from the common sensor node to the selected cluster head according to the following formula (3), and then the cluster head with the minimum Euclidean distance is added; the calculation formula of the euclidean distance is as follows:
E＝dist(C,x)2 (3)
c represents a cluster head, and x represents a common sensor node in the cluster;
(2.3) selecting an auxiliary Cluster head
After the number and the positions of the cluster heads are determined, each cluster head in the cluster serves as a main cluster head of the cluster; the task of the main cluster head is to collect sensed data of common sensor nodes in the cluster, then perform data fusion and data fragmentation, and then send the fragmented data to the auxiliary cluster head;
the auxiliary cluster heads are divided into two types, one type is the auxiliary cluster head which receives the data sent by the main cluster head and transmits the received data to the base station upwards; the other is an auxiliary cluster head which does not receive the data sent by the main cluster head, a false data packet is generated and is upwards transmitted to the base station together with real data packets of other auxiliary cluster heads;
the selection of the auxiliary cluster head is selected according to the residual energy of the node and the distance between the node and the base station, the influence factor of the auxiliary cluster head is A, the larger the value of A is, the higher the probability of being selected as the auxiliary cluster head is, and the calculation formula of A is as follows:
Figure FDA0003202578780000021
Eleftis the residual energy of the node, b is a constant, dtoBSIs the node-to-base station distance.
2. The method for protecting location privacy based on the clustering structure in the underwater acoustic sensor network according to claim 1, wherein: in the step (1):
setting an area 200m away from the ocean surface as a dynamic layer, and setting an area more than 200m away from the ocean surface as a static layer; the important equipment is anchored on the seabed of a static layer, sensor nodes of the static layer are clustered at first, a main cluster head and an auxiliary cluster head are selected, data collected by common sensor nodes are upwards transmitted to a dynamic layer by means of the main cluster head and the auxiliary cluster head, and then the data are routed to a base station.
3. The method for protecting location privacy based on the clustering structure in the underwater acoustic sensor network according to claim 1, wherein: the specific steps of the step (3) are as follows:
(3.1) Intra-Cluster data transfer
After the main cluster head and the auxiliary cluster heads are determined, other nodes in the cluster send sensed data to the main cluster head, the main cluster head performs data fusion, data fragmentation is performed after the data fusion of the main cluster head is completed, then the data are transmitted to a plurality of randomly selected auxiliary cluster heads, and the auxiliary cluster heads transmit upwards; generating false data packets by the rest auxiliary cluster heads and sending the false data packets upwards;
(3.2) data transfer at the interface between static and dynamic layers
1) If the auxiliary cluster head cannot sense the AUV of the dynamic layer within the communication range, the auxiliary cluster head transmits the data packet to the nearest node of the dynamic layer, and if the nearest node of the dynamic layer cannot sense the AUV of the dynamic layer within the time t, the auxiliary cluster head directly transmits the data packet to the base station;
2) if the auxiliary cluster head does not sense the AUV of the static layer in the communication range of the auxiliary cluster head, the auxiliary cluster head transmits a data packet to the nearest node of the dynamic layer, and if the nearest node of the dynamic layer senses the AUV of the dynamic layer within the time t, the AUV of the dynamic layer floats to the base station to transmit the data packet to the base station; 3) the auxiliary cluster head senses a static layer AUV in a communication range of the auxiliary cluster head, the auxiliary cluster head sends a data packet to the static layer AUV, the static layer AUV floats to a junction of the static layer and a dynamic layer, the data packet is sent to the dynamic layer AUV, and the dynamic layer AUV floats to a base station to send the data packet to the base station;
(3.3) Multi-hop data Transmission
If the node of the dynamic layer can not sense the AUV of the dynamic layer in the communication range within the time t, the node directly transmits a data packet to a base station, and the process is realized by utilizing a neighbor list of the node; each node is provided with a neighbor list which is updated regularly, and the stored content of the neighbor list is the hop number of the node and the neighbor nodes to reach the base station;
when a next hop is selected in the process of transmitting a data packet to the base station by the node, selecting any node which is smaller than or equal to the hop count of the node from the base station in the neighbor list until the node which has only one hop away from the base station is transmitted, and directly transmitting the data packet to the base station by the node;
(3.4) AUV data transfer
The path of the AUV is planned based on Q-learning, and the AUV walks in the underwater acoustic sensor network according to the planned path by establishing an environment state model, a behavior action model and a reward function model.
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