Research On Virus Transmission Model In Social Internet Of Things

The introduction of the social Internet of Things(SIoT)paradigm opens a new path for the development of the next generation of IoT,but it brings new security risks.Intelligent devices in SIoT are required to be open to cooperation,which further provides the chance for malicious attacks.Moreover,social attributes in social IoT accelerated the spreading of virus.It is important to find out the virus propagation features and influencing factors on the aspect of social attributes in SIoT.In view of two social attributes(i.e.,intelligent device's dissemination capacity and discriminant ability),this paper mainly contains several aspects:(1)In terms of device's dissemination capacity,this paper presents two kinds of calcu-lation methods.The first method makes great improvements on the K-shell decomposition algorithm.This improved algorithm considers not only the device's own dissemination capacity(i.e.,topological position)but also the contribution of neighboring devices on information dissemination.Moreover,those neighboring devices are classified into four groups according to K-shell decomposition deletion sequence and K-shell value.The second method presents a new algorithm(i.e.,DKs-HN)to measure the dissemination capacity based on the evidence theory and an improved K-shell method.The DKS-HN algorithm merges the direct influence of a particular node and the indirect influence of 1-hop neighbors by utilizing the combination rules of evidence theory.(2)The difference of device's discriminant ability can directly affect the probability of activation of the virus,and two methods are proposed to calculate discriminant ability.The first method takes into account a variety of factors,it divides device's discriminant ability into the rational discriminant ability and the irrational discriminant ability based on the sociological theory,and the calculation of the former is mainly realized by utilizing the PageRank idea.The second method proposes a Pvirus method to measure the second attribute based on the social hierarchy theory and the nonnegative matrix factor method.Every intelligent device can identify its trust relationship with other devices by using the Pvirus,and then the probability of virus activation lurking in devices can be predicted.(3)This paper integrates the solutions of social properties of the Internet of things.This paper proposes a dynamic virus propagation model(i.e.,IDEDSR),which focuses on two social attributes(i.e.,intelligent device's dissemination capacity and discriminant ability).The IDEDSR uses the DKS-HN algorithm and the Pvirus method to calculate the dissemination capacity and discriminant ability.A real dataset is used to simulate a social-aware IoT environment.Convincing experimental results show that the IDEDSR is more reasonable in design and good in performance.The IDEDSR performs better in controlling the virus propagation than the other five models.This paper also proposes a IoT-VSI model(IoT-Virus with dissemination capacity and discriminant ability).The IoT-VSI model adopts the first calculation method of each social attribute.This paper applies the mean-field equation theory to analyze the dynamic characteristics of virus propagation theoretically.