Paper Title
Content Trusted Scale: An Algorithm to Evaluate The Trustworthiness of A Website

Abstract
According to the minimum-security concepts of information security, the service provider of a website must ensure confidentiality, integrity, availability, non-repudiation, and access control. These concepts provide risk free access, but they cannot ensure truthfulness of the contents. Trust plays an important role in our life, whether it is with our colleagues, friends, or family. It is the same case when we use the Internet as an information system resource. We need to trust the information and avoid any spurious or incomplete resources. The Internet is used as an information system resource where billions of websites exist and exchange information. Sometimes we get confused regarding which information to accept and which to reject. Every site has a different style of presenting data, and when we surf the Internet, we find that the same topic is being discussed by number of sites using different ways to present data. Often, the data is contradictory. Therefore, we must have a novel algorithm to eliminate low quality and untrusted resources in order to provide quality contents for the readers. Many techniques have been presented to overcome trust issues but most of them only focus on authentication and reputation of the websites than the offered content. Consequently, in our paper, we expanded the work in order to build an algorithm that can be used online to gage the trust score of the content provided on a particular site and to minimize or quantify the errors and faulty information given to users. Using recommender systems and semantic web approach, the proposed algorithm will solve this issue. This paper defines trusting the contents of a website using a new algorithm. To overcome trust issue, we have devised a way in which we can match and rank the web resources provided by a website using recommender systems and semantic web. At the end of this paper, we will see how much confident the algorithm introduced to the websites. Keywords- Trusted websites, Content trusted scale, websites evaluation, websites ranking, recommender system matching and ranking, semantic web.