Research On D2D Communication Strategy With Data Security Protection

With the demand for wireless spectrum resources has increased dramatically,in order to improve the utilization of spectrum resources and ease the load on the base station,the 3rd Generation Partnership Project(3GPP)proposes Device-to-Device(D2D)technology to communicate directly with neighboring users through the licensed frequency band.However,as a brand new network architecture,the direct link nature of D2D communication makes it vulnerable to attacks.In the process of user communication,a malicious attacker may steal the communication data through a direct link and discard it at random.While causing network damage,the user's privacy security cannot be guaranteed.Therefore,secure D2D communication is very important to improve network performance and enhance user experience.In view of the above problems,the thesis studies the attack detection and privacy protection strategies in secure D2D communication.By introducing the basic concepts and application scenarios of D2D communication,and summarizing the research status and research hotspots,meanwhile analyzing the secure D2D communication strategy with attack detection and privacy protection,the security problems and existing mechanisms of D2D communication are elaborated.Firstly,a malicious D2D communication strategy based on behavioral awareness is proposed.By analyzing user behaviors,sensing user relationships,and combining data forwarding rates to distinguish differences between malicious users and ordinary users in data forwarding behavior,Elman neural networks are used to screen out users with malicious attacks and remove them from the network,while calculating trust value of common users.When a D2D user requests communication,the trust center assigns a user with a higher trust value to complete secure D2D communication.Numerical results show that the proposed strategy can improve the D2D communication security more effectively while improving the delivery rate.Secondly,a secure D2D communication strategy with data privacy protection is proposed in this thesis.Through the analysis of user attributes,when the D2D user requests group communication,the service center uses the pseudonym to ensure the user identity privacy and security,and at the same time,establishes a more reliable D2D communication group according to the similarity between users,and then uses the user attribute to establish more reliable D2D communication group.The D2D user's data transmission process performs key management to ensure that user data privacy is not stolen by malicious use by utilizing user attributes.The numerical results show that the proposed strategy can protect users' data privacy and security more effectively while ensuring successful communication.Finally,the work of this thesis is concluded and the future research work plan is presented.