Anapproach for empowering the hunt engine with controlling wormholes

Now a day's search engines in addition with the social networks try to attract the user and acquire their information by grabbing their attention towards a malicioussite. However theyare alsocapable ofspreading viruses introduced by intruders. For instance, a user publishes a post on a particular topic in which the malicious codes are hidden on a particular social networking site say Facebook, other social network users such as twitter users may search for that topic and subsequently visit those malicious pages. Through the search engine, now the malicious codes are then propagated from Facebook to twitter. Since the program is a virtual virus pool and creates propagation methods over the underlying network structure, the user doesn't gettoknow that the virus is being propagated. Therefore, we quantitatively analyse virus propagation effects and the stability of the virus propagation method within the presence of a search engine in social networks. At first, however social networks have a group structure that hinders virus spread, it is watched that the internet search engine produces a propagation hole. Then, a plague feedback model is being proposed and using four metrics i.e. infection density, the propagation hole result, the epidemic threshold and the basic replica variety the propagation effects are quantitatively analysed. Then, basedonfour real-world knowledge sets and two simulated knowledge sets the analyses are verified. Moreover, an attempt is made to prove that the planned model has the property of partial stability. Finally, the analysis results show that the program incorporates a higher infection density, bigger basic replica variety, shorter network diameter, bigger propagation speed and lower epidemic threshold.