A detection method for malicious nodes in sensor network based on energy field
A malicious node and detection method technology, applied in the field of communication, can solve the problems of increased threshold value, decreased detection accuracy, and no consideration of network node energy consumption, etc., to achieve the effect of prolonging energy consumption and improving accuracy
Active Publication Date: 2019-03-12
CHINA ELECTRIC POWER RES INST +2
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Problems solved by technology
[0004] (1) Did not consider how to make the energy consumption of network nodes more balanced
[0005] (2) The defined threshold formula is the energy consumption value of the node sending data. If the malicious node continues to send data, the corresponding threshold will become larger, thereby reducing the detection accuracy. Therefore, this method of defining the threshold needs to be improved
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[0050] The specific implementation manners of the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0051] In order to enhance the balance of energy consumption in the network and quickly and accurately detect malicious nodes that focus on energy consumption attacks, to ensure the availability of the network for a longer period of time. The present invention firstly considers the centripetality of the flow direction of the data packet in the wireless sensor network and the energy limitation of the nodes, and establishes a routing protocol based on the energy potential energy field on the wireless sensor network to form a sensor network based on the energy field; secondly, based on In the sensor network of the energy field, the ARMA prediction model is used to predict the energy consumption of the nodes, and then calculate the predicted value of the remaining energy of the nodes; finally, a dynamic threshold is selected ...
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The invention discloses a detection method for a malicious node in a sensor network based on an energy field, which includes the following steps: (1) constructing a wireless sensor network based on an energy field; (2) using an ARMA prediction model in the sensor network to Predict the remaining energy value of the node; (3) Energy-based malicious node detection. The invention constructs a sensor network based on an energy field to make energy consumption more balanced and effectively prolong the life of the network, and uses an ARMA prediction model with strong real-time performance to predict node energy, thereby improving the accuracy of security alarms. More importantly, the definition of the threshold in the prior art is calculated according to the energy consumption of nodes sending data. If the node is under attack and continues to send data, the threshold will become larger. The present invention adopts dynamic threshold selection and considers the The node becomes a factor that consumes a large amount of energy of the cluster head, which further improves the accuracy of detection.
Description
technical field [0001] The invention relates to the communication field, in particular to an energy field-based detection method for a malicious node in a sensor network. Background technique [0002] Wireless sensor network is a kind of wireless communication network with limited resources and centered on data. Nodes use batteries or other easily depleted power sources as power supply devices to make sensor nodes work normally. The entire network is usually in a harsh environment and completely exposed to in the enemy's field of vision. Therefore, how to balance the energy consumption among nodes to the greatest extent, save node energy consumption, avoid energy consumption attacks (such as DOS attacks, sinkhole attacks) and other security threats, and prolong the network life are the key issues in the study of wireless sensor network security applications. [0003] The patent "Wireless Sensor Network Intrusion Detection Method Based on Energy Prediction" includes the foll...
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IPC IPC(8): H04W12/00H04W84/18H04W12/122
CPCY02D30/70
Inventor 徐兴坤高昆仑赵婷郑晓崑徐志博
Owner CHINA ELECTRIC POWER RES INST