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An Insider Threat Categorization Framework for Automated Manufacturing Execution System

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Insider threats become one of the most dangerous threats in the cyber world as compared to outsider as the insiders have knowledge of assets. In addition, the threats itself considered in-visible and no one can predict what, when and how exactly the threat launched. Based on conducting literature, threat in Automated Manufacturing Execution Systems (AMESs) can be divided into three principle factors. Moreover, there is no standard framework to be referring which exist nowadays to categorize such factors in order to identify insider threats possible features. Therefore, from the conducted literature a standard theoretical categorization of insider threats framework for AMESs has been proposed. Hence, three principle factors, i.e. Human, Systems and Machine have considered as major categorization of insider threats. Consequently, the possible features for each factor identified based on previous researcher recommendations. Therefore, via identifying possible features and categorize it into principle factors or groups, a standard framework could be derived. These frameworks will contribute more benefit specifically in the manufacturing field as a reference to mitigate an insider threat.   Keywords—automated manufacturing execution systems insider threats, factors and features, insider threat categorization framework.
Title: An Insider Threat Categorization Framework for Automated Manufacturing Execution System
Description:
Insider threats become one of the most dangerous threats in the cyber world as compared to outsider as the insiders have knowledge of assets.
In addition, the threats itself considered in-visible and no one can predict what, when and how exactly the threat launched.
Based on conducting literature, threat in Automated Manufacturing Execution Systems (AMESs) can be divided into three principle factors.
Moreover, there is no standard framework to be referring which exist nowadays to categorize such factors in order to identify insider threats possible features.
Therefore, from the conducted literature a standard theoretical categorization of insider threats framework for AMESs has been proposed.
Hence, three principle factors, i.
e.
Human, Systems and Machine have considered as major categorization of insider threats.
Consequently, the possible features for each factor identified based on previous researcher recommendations.
Therefore, via identifying possible features and categorize it into principle factors or groups, a standard framework could be derived.
These frameworks will contribute more benefit specifically in the manufacturing field as a reference to mitigate an insider threat.
   Keywords—automated manufacturing execution systems insider threats, factors and features, insider threat categorization framework.

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