基于隐性社交关系的社交物联网信任评估模型  

Trust evaluation model of social internet of things based on implicit social relationship

作　　者：张红斌[1,2] 樊凡 赵冬梅 刘滨[3,4] 尹彦[1] 刘建 ZHANG Hongbin;FAN Fan;ZHAO Dongmei;LIU Bin;YIN Yan;LIU Jian(School of Information Science and Engineering,Hebei University of Science and Technology,Shijiazhuang 050018,China;Hebei Key Laboratory of Network and Information Security,Hebei Normal University,Shijiazhuang 050024,China;School of Economics and Management,Hebei University of Science and Technology,Shijiazhuang 050018,China;Research Center of Big Data and Social Computing,Hebei University of Science and Technology,Shijiazhuang 050018,China)

机构地区：[1]河北科技大学信息科学与工程学院,河北石家庄050018 [2]河北师范大学河北省网络与信息安全重点实验室,河北石家庄050024 [3]河北科技大学经济管理学院,河北石家庄050018 [4]河北科技大学大数据与社会计算研究中心,河北石家庄050018

出　　处：《网络与信息安全学报》2023年第2期56-69,共14页Chinese Journal of Network and Information Security

基　　金：国家自然科学基金(61672206,61572170);中央引导地方科技发展资金(216Z0701G);河北省科技支撑计划(18210109D,20310701D,20310802D,21310101D);国家文化和旅游科技创新工程(2020年度)。

摘　　要：社交物联网是社交网络和物联网融合形成的新范式,增强了网络的扩展性和可导航性。然而,由于智能设备的开放性和移动性增强,智能对象的信息安全、可靠服务提供等方面的安全风险进一步扩大,安全问题面临严峻挑战。信任被视为提供安全、可靠服务的关键因素,因此,从社交关系角度出发,提出了一种新的信任评估模型。提出一种信任传递算法,根据节点间的显性社交关系和潜在特征,挖掘并建立节点间的隐性社交关系,达到解决社交物联网网络稀疏性、冷启动问题的目的。对社交关系进行细粒度划分,构建单关系子网,并将多个单关系子网融合构建多重关系复合网,从而有效融合节点间多种动态变化的社交关系对信任评估的影响。根据直接信任、间接推荐信任及服务满意度3个信任指标对智能对象进行综合信任评估。通过在真实智慧城市数据集上的实验结果表明,无论是在不稀疏网络场景还是稀疏网络场景中,该模型都具有较好的鲁棒性,能够有效地评估网络中的可信对象和不可信对象,并提高信任评估的准确性和收敛性。The social internet of things(SIoT)is a new paradigm that combines social networks and the internet of things to enhance network scalability and navigability.However,with increased openness and mobility of intelligent objects,there are rising security risks related to information security and reliable service delivery,which poses a significant challenge to the SIoT.Trust is a critical factor in providing secure and reliable services.Therefore,a new trust assessment model was proposed from the perspective of social relationships.A trust transfer algorithm was proposed based on the explicit social relationships and potential features between nodes.The algorithm can tap and establish the implicit social relationships among nodes to solve the SIoT sparsity and cold start problem.Additionally,the social relations were fine-grained and divided to build a single-relationship sub-network.Multiple single-relationship sub-networks were fused to build a multiple-relationship composite network.Thus,the impact of multiple dynamically changing social relationships among nodes on trust evaluation can be effectively fused.The comprehensive trust assessment of intelligent objects was conducted based on three indicators:direct trust,indirect recommendation trust,and service satisfaction.The experimental results on real smart city datasets demonstrate the model’s robustness in non-sparse and sparse network scenarios.It can effectively evaluate trusted and untrusted objects in the network and improve the accuracy and convergence of trust evaluation.

关 键 词：隐性社交关系 多重社交关系 社交物联网 信任评估 

分 类 号：TN915[电子电信—通信与信息系统]