# Secure Internal Data Markets
## 6 Conclusions  
In this paper, we have analysed the differences between global and internal data markets with respect to security, outlining the issues that internal data markets face, but also the characteristics they have that could be used to potentially provide a higher level of security, especially considering the internal knowledge of the market owner on the traded data and the involved users. To the best of our knowledge, this is the first time global and local data markets were compared with respect to security in a structured way. Based on the results of this analysis, we see ample reasons for future research in this area, as most data markets concepts currently available typically focus on global approaches, even in cases where there is a limited number of foreseen partners. This, in our opinion, does not include all possible trust relationships between partners. Furthermore, the structure of the members and the partnerships has to be taken into account, especially considering such issues as insider attacks through highly connected partners. A special fundamental issue that needs to be taken into account as a conclusion is the status of an internal data market with respect to the rest of the institutions: while in the global market situation, the global data market is typically the core (business) unit, a local market will often only be a side attraction when compared to the core business of the company/ies in question. Thus, any issues surrounding this market will not receive the same level of attention as those in the global market scenario. On the other hand, there might be far better knowledge on the data handled through the market, providing more insight on the protection and mitigation mechanisms required.  
Based on this analysis, we provided a basic model for a secure internal data market that can be used as a starting point for generating specific market models that are tailored to the needs of the institution. Here, we observe a huge need for providing mechanisms that support the semi-automated generation of instances of specific local data markets based on the outlined model. This includes supporting the analysis of partners and their (trust) relationships but also issues surrounding the technical setup. Finally, we are of the opinion that the data market concept can work for many companies on a local basis; however, a lot of additional research is required in order to make it practical for smaller institutions.  
Conceptualisation, S.S. and P.K.; methodology, S.S.; validation, E.W. and P.K.; investigation, P.K. and S.S.; writing--original draft preparation, P.K. and S.S.; writing--review and editing, E.W.; project administration, P.K.; funding acquisition, S.S. All authors have read and agreed to the published version of the manuscript. This research was funded by the Austrian Research Promotion Agency grant number 866880 (Big Data Analytics) and grant number 880592 (Secure Internal Data Markets).  
Not applicable.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.