Research On The Data Forwarding Strategy For Defending Against Malicious Node Behavior In ICWN

Intermittently connected wireless network(ICWN)is a kind of self-organizing network that can be easily deployed without any fixed network infrastructure,therefore,it mostly used in emergency communications networking and military applications.The intermittently connected of nodes causes the network to lack end-to-end path,participating nodes can only communicate by means of "store-carry-forward" with the help of each other's encountering opportunities,thus,this kind of communication mode determines that the data forwarding requires multiple nodes to complete in a cooperative manner.However,the node energy and cache resources are scarce in the network,some selfish nodes often exhibit non-cooperative behavior in order to save resources.Moreover,there are some malicious nodes take the initiative to launch attacks in the network,damaging the network operation seriously.In order to avoid the impact of non-cooperative nodes on data forwarding,this thesis studies the secure data forwarding strategy with malicious node detection in ICWN.First of all,this thesis introduces the research background of ICWN from the aspects of network characteristics and application scenarios,then analyzes the current research hot spots of the network,and then researches the secure data forwarding strategy with trust management and attack detection.Furthermore,the key issues and basic principles of various classic trust management and attack detection methods are expounded.Secondly,aiming at the uncertainty of recommendation information,a data forwarding strategy that can detect the forged data produced by malicious recommendation nodes by using the consistency of interactive list is proposed.Furthermore,to aim at differences of the recommendation information,this thesis filters the error recommendation information to accurately evaluate the trust relationship between two nodes by the outlier detection method.Meanwhile,this thesis also achieves the efficient data forwarding by selecting the relay nodes accurately based on similarities between a meeting node and a destination node.At last,the simulation contrastive analysis shows that the proposed strategy can resist the malicious recommendation information effectively and improve the data delivery rate compared with other typical algorithms.Thirdly,aiming at the multi-node collusion attack,a data forwarding strategy with collusion nodes detection is proposed,which identifies the part of collusion nodes through the closed loop of unidirectional data paths and then uses the K-nearest neighbor classification algorithm to determine the maliciousness of the suspect nodes.Furthermore,according to the remaining resources and social capabilities to assess the node's data forwarding capabilities,it can be a basis for selecting a suitable relay node.The simulation contrastive analysis show that the proposed data forwarding strategy can effectively identify the collusion nodes and significantly improve the network performance compared with the same type of algorithms.Lastly,the research works are concluded and the future research works are presented.