A risk assessment method for negative SEO attacks using a game theoretic approach

Abstract

Search Engine Optimisation (SEO) is a form of Internet marketing that seeks to promote websites and apps by increasing their visibility in search engine result pages (SERPs). Techniques used by SEO practitioners who operate within the guidelines of the search engines are known as “white-hat” in contrast “black-hat” techniques are designed to manipulate search rankings. Negative SEO is a relatively new phenomenon whereby a third party applies SEO techniques that seek to exploit vulnerabilities in search engine ranking algorithms to negatively affect the ranking of a target website. Few risk assessment models and frameworks exist to address this threat. In this paper, we define negative SEO and categorise common classes of techniques deployed in negative SEO. A risk assessment framework is proposed for negative SEO using a game theoretic approach. We propose a model to determine the ideal offensive and defensive strategies for players in a negative SEO game. We provide a model to compare risks of negative SEO behavior using a semi-quantitative approach and a case study using a payoff matrix. As a result marketers and other technical communicators can determine which defensive SEO strategies should be taken to avoid negative outcomes resulting from a negative SEO attack.