However, this following snippet from the paper is something can be augmented and used for threat forecasting.
There are currently models that exist for scoring threats, as can be seen in the Scientific World Journal, which published the paper “Using a Prediction Model to Manage Cyber Security Threats.” Although this type of modeling is tied to CVSS and the risk associated within an organization based on multiple attributes. This is where you can pinpoint risk starting from a specific geographical location, to a city, an industry vertical, a specific corporation and, finally, an individual. These risk levels are tied to the KPIs, but more importantly to corresponding IP addresses of major corporations and small-to-medium businesses to email addresses. In addition to the build, buy and partner analysis you need to perform a statistical scoring analysis that provides the highest probability of the data to determine what would be considered low risk 0–30%, medium risk 31–79% and high risk 80–100%. This requires a build, buy and partner analysis. Since threat forecasting is a relatively new concept that provides the ability to forecast a threat before it arrives at the front door, you have to ensure that all the threat data are high fidelity. The M at the end of the file extension indicates that the document contains Macros.
SLDM-New file extensions introduced in Office 2007. PPT- Microsoft Word, Excel, and PowerPoint documents.
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