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ItemIntroducing the Factor Importance to Trust of Sources and Certainty of Data in Knowledge Processing Systems - A new Approach for Incorporation and Processing( 2017-01-04)In knowledge processing systems data is gathered from several sources. After some calculating and processing steps are taken in the system, a result is finally computed and may be used for further steps or by other systems. Most of the time the origin and provenance of input data is not verified. Using unverified data can cause inconsistencies in processing and generating output, and could lead to corrupting threats for the system and the environment as a whole. \ \ We propose an approach where several characterizing values in a given environment - trust of source, certainty of data, and importance (of data) in the current processing step - are used to compute new output characteristics of a knowledge processing system. These values represent the trustworthiness and the certainty of the output in multi-step processing systems based on all used sources and input data. We demonstrate the application of our approach on simple and advanced fictitious scenarios as well as on a real world scenario from the agricultural domain.
ItemCombating Phishing Attacks: A Knowledge Management Approach( 2017-01-04)This paper explores how an organization can utilize its employees to combat phishing attacks collectively through coordinating their activities to create a human firewall. We utilize knowledge management research on knowledge sharing to guide the design of an experiment that explores a central reporting and dissemination platform for phishing attacks. The 2x2 experiment tests the effects of public attribution (to the first person reporting a phishing message) and validation (by the security team) of phishing messages on reporting motivation and accuracy. Results demonstrate that knowledge management techniques are transferable to organizational security and that knowledge management can benefit from insights gained from combating phishing. Specifically, we highlight the need to both publicly acknowledge the contribution to a knowledge management system and provide validation of the contribution. As we saw in our experiment, doing only one or the other does not improve outcomes for correct phishing reports (hits).