Automatic Actionable Information Processing and Trust Management towards Safer Internet of Things

• Main Authors: Marek Janiszewski, Anna Felkner, Piotr Lewandowski, Marcin Rytel, Hubert Romanowski
• Format: Article
• Language: English
• Published: MDPI AG 2021-06-01
• Series: Sensors
• Subjects: Internet of Things (IoT); vulnerabilities; vulnerability database; exploits; TRM; trust
• Online Access: https://www.mdpi.com/1424-8220/21/13/4359

The security of the Internet of Things (IoT) is a very important aspect of everyday life for people and industries, as well as hospitals, military, households and cities. Unfortunately, this topic is still too little researched and developed, which results in exposing users of Internet of Things to possible threats. One of the areas which should be addressed is the creation of a database of information about vulnerabilities and exploits in the Internet of Things; therefore, the goal of our activities under the VARIoT (Vulnerability and Attack Repository for IoT) project is to develop such a database and make it publicly available. The article presents the results of our research aimed at building this database, i.e., how the information about vulnerabilities is obtained, standardized, aggregated and correlated as well as the way of enhancing and selecting IoT related data. We have obtained and proved that existing databases provide various scopes of information and because of that a single and most comprehensive source of information does not exist. In addition, various sources present information about a vulnerability at different times—some of them are faster than others, and the differences in publication dates are significant. The results of our research show that aggregation of information from various sources can be very beneficial and has potential to enhance actionable value of information. We have also shown that introducing more sophisticated concepts, such as trust management and metainformation extraction based on artificial intelligence, could ensure a higher level of completeness of information as well as evaluate the usefulness and reliability of data.