Research On Attacks Detection In Wireless Sensor Networks

Recent advances in microelectronics,computer technology and wireless communication technology have enabled wireless sensor networks(WSNs) to be gradually used in military,environmental monitoring and other areas.However,the openness of transmission media and the harsh environment of deployment threat the security of WSNs and restrict applications of WSNs.How to ensure the safety of information transmission and maintain the normal work of the networks become serious questions when WSNs designed.There exists many types of attacks threatening WSNs,among these attacks, selective forwarding attacks is a usual and fundamental attack,many other attacks gain benefit from it.Furthermore,false data injection attacks from internal node is also very difficult to perceive and discover.Therefore,we choose selective forwarding attacks and false data injection attacks as our study objects.The main contributions of my dissertation include:(1) According the drawbacks of existing method for selective forwarding attacks, a novel detection method which based on trust degree and behavior of packet loss is put forward.Reporting packets which include number of receiving and forwarding packets on the path are sent for base station from nodes,then the base station calculate the quantity of lost packets.We introduce trust mechanism into our method and designate the node's influence on entire packets lost on the path as its trust degree. The method updates the node's trust degree periodically.Combined with behavior evaluation,the method detects the malicious node eventually.The method can achieve relatively high detection rate,avoid complicated encryption and hardware facilities.(2) According the shortcomings of existing detection schemes for false data injection attacks,a method based on fitted data is proposed.To find out the law of decaying of senor data with node's position,the senor data is fitted first,then the method compares the actual sensor data with the law and judge whether there occurs false data injection attacks.The methods can detect the attacks from source node without sophisticated key distribution scheme.(3) The selective forwarding attacks detection method based on trust degree and behavior is simulated in TOSSIM using nesC which is a component-based programming language.The false data injection attacks detection mechanism based fitted data is also simulated.The performance of detection mechanisms are compared with the existing schemes for attacks,which validates the validities of two attack detection methods.