# Blockchain-Based Model for Incentivized Cyber Threat Intelligence Sharing
## 3 Proposed Solution
### Building of Motivation and Trust
#### 3.2.2 Choice of Data Quality Metrics for Reviewers  
CTI data consumers are encouraged to write a review of the data and present it to the CTI data producer. To guide the reviewers, an investigation was carried out to select the appropriate metrics for CTI quality evaluation. [PERSON] et al. [24] divided CTI quality factors into three groups: quality metrics, quality of the collected data, and quality of the produced intelligence. [PERSON] et al. [25] later categorized the CTI quality factors into three groups again; however, only the quality of collected data and quality of produced intelligence groups remained the same. The quality of collected data group [24; 25] is only based on two publications [26; 27]. In contrast, [PERSON] [27] wrote that the factors of relevance, actionability, and value characterize the produced intelligence. We suppose that [PERSON] et al. [24; 25] wrongly attributed these factors to the group of collected data. Moreover, relevance is defined as showing the relation of information to a specific organization's environment and aligning it with the organization's priorities and objectives. Thus, if the reviewer presents a different domain than the CTI data presented, the organization perceives such CTI data as irrelevant. We suppose that such an assessment would not be fair. Therefore, we seek metrics that are unrelated to the specifics of the field of CTI data; in particular, this requirement is fully satisfied by the quality metrics presented by [PERSON] et al. [26].  
Other CTI data quality metrics [28; 29] are available as well. [PERSON] et al. [28] presented a hierarchical quality metric consisting of three levels: report, object, and attribute. These are quite complex and detailed metrics for ordinary reviewers. Moreover, these metrics are STIX-format-oriented. The attribute level is entirely based on the evaluation of the available STIX objects.  
[PERSON] et al. [29] introduced quality metrics that include the following factors: completeness, freshness, timeliness, extensiveness, and relevance. These metrics are tool-oriented, and the values of all of the factors are calculated automatically. However, [PERSON] et al. [29] noticed that the calculation of completeness, freshness, and extensiveness requires improvement.  
We reviewed many studies relevant to the topic in this section; however, only [PERSON] et al. [15] and [PERSON] et al. [19] considered the use of quality metrics for the verification of CTI data. The metrics of consideration used in [15] were presented by [PERSON] et al. [28]. However, [PERSON] et al. [19] provided neither a reference to specific metrics nor a detailed description of the metrics used. Only the factors of accuracy, usability, and relevance were mentioned. In addition, their future work was to determine which quality metrics are appropriate for CTI data verification. Moreover, a verified security expert evaluated the quality of CTIdata in both approaches [15; 19]. We suppose that the metric [28] is too complicated for the ordinary reviewer. Therefore, after careful consideration, we decided to present the quality factors introduced by [PERSON] et al. [26] to the reviewers, as follows: accuracy, timeliness, completeness, and consistency. These factors are common to many data domains [8].