A survey of new orientations in the field of vehicular cybersecurity, applying artificial intelligence based methods

Nowadays, cybersecurity is an emerging research area in the automotive industry, and it is investigated by many different perspectives. Our article is a review of existing vehicular security solutions that covers the state‐of‐the‐art and future research directions. This article is a new contribution to tutorials/surveys related to the vehicular cybersecurity domain with the latest details. We developed a database from 140 articles from the field of automotive security. In the database, we assigned specific attributes to every article (such as Web of Science Impact Factor or the number of citations). The data set was analyzed by the K‐means clustering and decision tree analysis methods to identify and characterize the generated groups of papers. Following this, the article highlights the research areas that might receive more attention in the future. Accordingly, the result of the current research can be applied by the decision‐makers, researchers, and Original Equipment Manufacturers to allocate additional resources to those domains, which is expected to shape the future of vehicular security. This vehicular cybersecurity survey analyzes and highlights the research topics/areas which might or should receive more attention in the future, based on analytical AI models (K‐means clustering, decision tree analysis).