CN103619011A - Method for tolerating malicious nodes in wireless sensor network - Google Patents

Abstract

The invention discloses a malicious node tolerance method in a wireless sensor network, which changes the traditional security protection method based on encryption, authentication and trust model, and actively protects by actively destroying malicious nodes to achieve the purpose of attack tolerance. The energy of malicious nodes is consumed by transmitting meaningless data in the network. In the state of attack tolerance, normal nodes only generate energy consumption when sending data, while malicious nodes are always in the radio frequency working state. With the small energy consumption of all normal nodes In exchange for the large energy consumption of malicious nodes so that they cannot work. On the premise of ensuring the normal data communication of the sensor network, the effective protection of malicious nodes is completed, which provides a new idea for the secure communication of the wireless sensor network.

Description

A Malicious Node Tolerance Method in Wireless Sensor Networks

technical field

The invention relates to a malicious node attack tolerance method in a wireless sensor network, belonging to the fields of wireless communication and network security.

Background technique

In recent years, with the development and integration of sensor, computer, wireless communication, micro-electromechanical and other technologies, wireless sensor networks (WSN: wireless sensor networks) have emerged. People can finally monitor the external environment in real time and realize large-scale and automated information. collection. WSN has broad application prospects in military and civilian fields such as military reconnaissance, environmental monitoring, medical monitoring, space exploration, urban traffic management, and warehouse management.

A wireless sensor network is composed of a large number of sensor nodes with limited battery energy, computing power, storage capacity, and communication capabilities. If the network nodes are uncontrollable (for example, enemy war zone) or the WSN scale is large, then the nodes will be arranged randomly. Since WSN is a wireless communication, an attacker can easily monitor the channel in the task domain of the network, inject bit stream into the channel, and replay the previously monitored data packets. In addition, if the sensor is randomly deployed in the unattended external space, the attacker can easily capture the node, rewrite the memory, or replace the node with his own sensor, and obtain data information by posing.

However, due to the limitations of its own resources and computing power, WSN's security faces more severe challenges than ordinary computer network security. Therefore, a more effective security prevention mechanism is needed.

At present, malicious nodes in some wireless sensor network models are assumed to have unlimited energy and resources, but this assumption is often not true in practical applications. In the actual wireless sensor deployment scenario, unlimited energy and resources are almost impossible. Realized, this is only applicable to wired network scenarios. Therefore, for malicious nodes, there is also the situation that they cannot work when the energy is exhausted.

The attack methods of malicious nodes in the sensor network include selective forwarding, data tampering, replay and DOS attacks, etc. If malicious nodes want to carry out the above attacks, when there is data packet transmission in the network, the radio frequency circuit must be in working condition, otherwise Unable to achieve its attack purpose. The working time of the radio frequency circuit of the malicious node determines its life cycle, so that the malicious node works in the radio frequency transmitting and receiving state for a long time so that its energy will be exhausted quickly to achieve the purpose of tolerating the attack.

For wireless sensor nodes, the energy consumption is mainly in the control circuit and the radio frequency circuit, and the power consumption of the radio frequency circuit in the transmitting or receiving state is generally 3 to 6 times that of the control circuit. How to effectively make the wireless sensor nodes coordinate their dormant state (turn off the radio frequency circuit) in their work is the key to ensure the long-term effective operation of the entire network.

Contents of the invention

Technical problem: In order to overcome the deficiencies in the prior art, the present invention proposes a malicious node tolerance method in a wireless sensor network. Aiming at the operating characteristics of malicious nodes, normal nodes in a wireless sensor network can Work, so that the energy of malicious nodes is quickly exhausted, and the purpose of tolerating and destroying malicious nodes is achieved.

Technical scheme: in order to achieve the above object, the technical scheme adopted in the present invention is:

A malicious node tolerance method in a wireless sensor network, comprising the steps of:

(1) The base station sends an attack tolerance command to the entire network, and the command message is transmitted in the network in a flooding manner, and each normal node in the sensor network is ready to enter the attack tolerance state from the normal working state after receiving the command;

(2) The normal node i (i=1,2,...N) enters the attack tolerance state, and N represents the number of nodes in the wireless sensor network. Node i respectively sets two timers T _i1 and T _i2 , and a random number of wake-ups W _i , where W _i is determined according to the number of attacking nodes in the network, when the attacking node is uncertain, set W _i =3, W _i increases as the number of attacking nodes in the network increases, T _i1 represents the total time for node i to enter the attack-tolerant state, T _i2 represents the time for node i to wake up for the first time, and T _i1 >W _i ·T _i2 ;

(3) Node i turns off the radio frequency circuit, and enters sleep mode according to the time set by T _i1 , when the sleep time reaches T _i2 , node i wakes up and turns on the radio frequency circuit, and sends random data packet D to the network. After the data packet D is sent, W _i =W _i -1, T _i1 =T _i1 -T _i2 , node i recalculates T _i2 to satisfy T _i1 >W _i ·T _i2 , and sets T _i1 and T _i2 ;

(4) Repeat step (3) until W _i =0, node i turns off the radio frequency circuit, and enters the sleep mode according to the time set by T _i1 ;

(5) When the sleep time reaches T _i1 , node i wakes up and turns on the radio frequency circuit, and re-enters the normal working state.

The malicious node tolerance method in the wireless sensor network can be used in the normal working state of the sensor network, and all nodes of the sensor network alternate between the normal working state _SN and the attack tolerant state _ST periodically. The alternate cycle time is determined by the sensor network's requirement for real-time data. The higher the real-time requirement, the longer the time of _SN is than the time of _ST . On the contrary, the time of _ST is longer than the time of _SN .

The time in the normal working state _SN and the attack tolerant state _ST can be set during network initialization, and can also be adjusted in real time according to changes in data real-time requirements.

The malicious node tolerance method in the wireless sensor network does not perform data and routing information interaction when all network nodes are in the attack tolerance state _ST .

The malicious node tolerance method in the wireless sensor network can be implemented by clustering in a network that requires high real-time data. Each cluster independently runs the malicious node tolerance method, and the cluster head sends the attack tolerance command to the nodes in its own cluster, and then each node in the cluster runs a complete attack tolerance method, and each cluster head is still in the normal working state, receiving and caching Data or routing requests from the upper layer interact with the nodes in the cluster when the cluster enters the normal working state.

In the clustering method to realize malicious node tolerance in the wireless sensor network, the cluster heads in each cluster need to perform cluster head rotation according to their own energy and resource conditions to ensure the balance of node energy and resources.

The malicious node tolerance method in the wireless sensor network can be used in conjunction with the intrusion detection method of the malicious node. When the intrusion detection method does not detect the malicious node, all nodes in the sensor network maintain the original state of work; when the intrusion detection method detects the malicious node When the nodes are connected, the sensor network enters the alternation of normal working state and attack tolerance state. With the exclusion of malicious nodes, the network returns to its original working state.

Beneficial effects: the present invention provides a malicious node tolerance method in a wireless sensor network, which changes the traditional security protection method based on encryption, authentication and trust models, and actively protects by actively destroying malicious nodes to achieve the goal of attack tolerance. The energy of malicious nodes is consumed by transmitting meaningless data in the network. In the state of attack tolerance, normal nodes only generate energy consumption when sending data, while malicious nodes are always in the radio frequency working state. With the small energy consumption of all normal nodes In exchange for the large energy consumption of malicious nodes so that they cannot work. On the premise of ensuring the normal data communication of the sensor network, the effective protection of malicious nodes is completed, which provides a new idea for the secure communication of the wireless sensor network.

Description of drawings

Fig. 1 is the flowchart of the inventive method;

Fig. 2 is the flowchart of the inventive method in the clustering network;

Fig. 3 is the working sequence chart of normal node among the present invention;

Fig. 4 is a working sequence diagram of a normal node combined with an intrusion detection method in the present invention;

Fig. 5 is a graph of node energy consumption after using the method of the present invention.

Detailed ways

The present invention will be further described below in conjunction with the accompanying drawings.

As shown in Figure 1, it is a flow chart of a malicious node tolerance method in a wireless sensor network in a clustering network, including the following steps:

(1) The base station sends an attack tolerance command to the entire network, and the command message is transmitted in the network in a flooding manner, and each normal node in the sensor network is ready to enter the attack tolerance state from the normal working state after receiving the command;

(2) The normal node i (i=1,2,...N) enters the attack tolerance state, and N represents the number of nodes in the wireless sensor network. Node i respectively sets two timers T _i1 and T _i2 , and a random number of wake-ups W _i , where W _i is determined according to the number of attacking nodes in the network, when the attacking node is uncertain, set W _i =3, W _i increases as the number of attacking nodes in the network increases, T _i1 represents the total time for node i to enter the attack-tolerant state, T _i2 represents the time for node i to wake up for the first time, and T _i1 >W _i ·T _i2 ;

(3) Node i turns off the radio frequency circuit, and enters sleep mode according to the time set by T _i1 , when the sleep time reaches T _i2 , node i wakes up and turns on the radio frequency circuit, and sends random data packet D to the network. After the data packet D is sent, W _i =W _i -1, T _i1 =T _i1 -T _i2 , node i recalculates T _i2 to satisfy T _i1 >W _i ·T _i2 , and sets T _i1 and T _i2 ;

(4) Repeat step (3) until W _i =0, node i turns off the radio frequency circuit, and enters the sleep mode according to the time set by T _i1 ;

(5) When the sleep time reaches T _i1 , node i wakes up and turns on the radio frequency circuit, and re-enters the normal working state.

As shown in Figure 2, it is a flowchart of a malicious node tolerance method in a wireless sensor network, including the following steps:

(1) The base station sends an attack tolerance command to the cluster head nodes of the entire network, and the command message is transmitted in the network in a flooding manner, and the cluster head nodes in each sensor network receive the command;

(2) Each cluster head node sends an attack tolerance command to each sensor node in the cluster, and the normal nodes in each cluster are ready to enter the attack tolerance state from the normal working state after receiving the command;

(3) The normal node i (i=1,2,...N) in the cluster enters the attack tolerance state, and N represents the number of nodes in the cluster. Node i respectively sets two timers T _i1 and T _i2 , and a random number of wake-ups W _i , where W _i is determined according to the number of attacking nodes in the cluster, and when the attacking node is uncertain, set W _i =3 , W _i increases with the number of attacking nodes in the network, T _i1 represents the total time for node i to enter the attack-tolerant state, T _i2 represents the time for node i to wake up for the first time, and T _i1 >W _i ·T _i2 ;

(4) Node i turns off the radio frequency circuit, and enters sleep mode according to the time set by T _i1 , when the sleep time reaches T _i2 , node i wakes up and turns on the radio frequency circuit, and sends random data packet D to the network. After the data packet D is sent, W _i =W _i -1, T _i1 =T _i1 -T _i2 , node i recalculates T _i2 to satisfy T _i1 >W _i ·T _i2 , and sets T _i1 and T _i2 ;

(5) Repeat step (3) until W _i =0, node i turns off the radio frequency circuit, and enters the sleep mode according to the time set by T _i1 ;

(6) When the sleep time reaches T _i1 , node i wakes up and turns on the radio frequency circuit, and re-enters the normal working state.

As shown in Figure 3, it is a working sequence diagram of a normal node using the malicious node tolerance method of the present invention. It can be seen from the figure that the normal node alternates between the normal working state and the attack tolerant state with a period of T, and the normal working state The time in the state is T ₁ , and the time in the attack-tolerant state is T ₂ . T ₁ and T ₂ are adjusted according to the actual application environment of the sensor network and the situation of the attack node. The larger T ₂ is, the better the tolerance to malicious nodes is, but the real-time performance of network data communication will decrease.

As shown in Figure 4, it is a working sequence diagram of a normal node in conjunction with an intrusion detection method in the present invention, as can be seen from the figure, a normal node simultaneously performs intrusion detection of a malicious node in a normal working state, and the time in this state is T ₁ , when a normal node detects the existence of a malicious node, it will notify the base station or the cluster head to make all normal nodes enter the attack tolerance state, so T ₁ is not fixed, if no malicious node is detected in the network, then the normal node has been in normal work and intrusion detection state. The time that the node is in the attack tolerance state is T ₂ , and T ₂ is a fixed value. With the exclusion of malicious nodes, the network returns to its original working state.

In a specific embodiment, we assume that there are 100 normal nodes and 1 malicious node in the wireless sensor network, and the malicious node is within the radio frequency coverage of 10% of the normal nodes, that is, it can communicate with 10 normal nodes. After the malicious node receives the data packet from the normal node, it will forward it twice. In order to illustrate the function of the method of the present invention, it is necessary to quantify the energy consumption value of the nodes. Taking CC2530 as the main chip of the sensor node as an example, suppose its working clock frequency is 32MHz, the working current of CPU is 6.5mA, the working current of RF receiving is 24.3mA, and the working current of RF transmitting is 33.5mA. The operating current to start a timer interrupt is 90uA.

The node works according to the normal node working timing diagram shown in Figure 3, T ₁ =1s, T ₂ =4s, and respectively take W=3 and W=30 for the test, observe for 100s, the results are shown in Figure 5, horizontal The coordinate is time, the unit is s, and the ordinate is power consumption, the unit is mAs. It can be seen from the figure that the lower curve shows that the power consumption of normal nodes is very small, so the method of the present invention hardly increases the energy consumption of normal nodes, while the upper two curves represent the power consumption of malicious nodes. The energy consumption is hundreds of times that of normal nodes. The larger W is, the faster the energy consumption of malicious nodes will be. With the increase of working time, using the method of the present invention will rapidly consume the energy of malicious nodes, making them unable to operate, and for a network with more malicious nodes, the effect of the method of the present invention is better.

The above is only a preferred embodiment of the present invention, it should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, some improvements and modifications can also be made, and these improvements and modifications are also possible. It should be regarded as the protection scope of the present invention.

Claims (7)

1. A malicious node attack tolerance method in a wireless sensor network, characterized in that: the method comprises the steps: 1) The base station sends an attack tolerance command to the entire network, and the command message is transmitted in the network in a flooding manner, and each normal node in the sensor network is ready to enter the attack tolerance state from the normal working state after receiving the command; 2) The normal node i enters the attack tolerance state, i=1, 2,...N, N represents the number of nodes in the wireless sensor network, and the node i sets two timers T _i1 and T _i2 respectively, And a random wake-up times W _i , where W _i is determined according to the number of attacking nodes in the network, when the attacking nodes are uncertain, set W _i =3, W _i increases with the increase of the number of attacking nodes in the network, T _i1 represents the total time for node i to enter the attack tolerance state, T _i2 represents the time for node i to wake up for the first time, and T _i1 >W _i ·T _i2 ; 3) Node i turns off the radio frequency circuit, and enters the sleep mode according to the time set by T _i1 . When the sleep time reaches T _i2 , node i wakes up and turns on the radio frequency circuit, and sends a random data packet D to the network, and the sending of data packet D is completed Afterwards, W _i =W _i -1, T _i1 =T _i1 -T _i2 , node i recalculates T _i2 to satisfy T _i1 >W _i ·T _i2 , and sets T _i1 and T _i2 ; 4) Repeat step 3) until W _i =0, node i turns off the radio frequency circuit, and enters the sleep mode according to the time set by T _i1 ; 5) When the sleep time reaches T _i1 , node i wakes up and turns on the radio frequency circuit, and re-enters the normal working state. 2. the malicious node attack tolerance method in a kind of wireless sensor network according to claim 1, it is characterized in that: this method is used under the state that sensor network works normally, and all nodes of sensor network are in normal work state periodically _SN and attack-tolerant state _ST alternate, and the cycle time of the alternation is determined by the real-time requirements of the sensor network for data. The higher the real-time requirements, the time of _SN is longer than the time of _ST , otherwise, the time of _ST is longer. Time greater than _SN . 3. the malicious node attack tolerance method in a kind of wireless sensor network according to claim 2, it is characterized in that: the time under described normal working state _SN and attack tolerance state _ST is set during network initialization, Or make real-time adjustments according to changes in data real-time requirements. 4. A malicious node attack tolerance method in a wireless sensor network according to claim 1, characterized in that: the method does not perform data and routing information interaction when all network nodes are in an attack tolerance state. 5. the malicious node attack tolerance method in a kind of wireless sensor network according to claim 1, it is characterized in that: this method adopts the method for clustering to realize in the network that real-time data is required very high; Run the malicious node tolerance method independently, the cluster head sends the attack tolerance command to the nodes in its own cluster, and then each node in the cluster runs the complete attack tolerance method, each cluster head is still in the normal working state, receiving and caching the data from the upper layer Data or routing requests, when the cluster enters the normal working state, it interacts with the nodes in the cluster. 6. The malicious node attack tolerance method in a wireless sensor network according to claim 5, characterized in that: the clustering method realizes that in the malicious node tolerance method in the wireless sensor network, the cluster heads in each cluster It is necessary to perform cluster head rotation according to its own energy and resource conditions to ensure the balance of node energy and resources. 7. The malicious node attack tolerance method in a wireless sensor network according to claim 1, characterized in that the method is used in conjunction with the intrusion detection method of the malicious node, when the intrusion detection method does not detect the malicious node, in the sensor network All nodes in the sensor network maintain the original state; when the intrusion detection method detects malicious nodes, the sensor network enters the alternation of normal working state and attack tolerance state. With the exclusion of malicious nodes, the network returns to its original working state.

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