Deriving Candidate Technical Controls and Indicators of Insider Attack from Socio-Technical Models and Data
Year: 2023
Type: report
Abstract: The insider threat continues to be one of the prime issues facing government entities and organizations across critical infrastructure sectors. Extensive catalogues of case material from actual insider events have been used by CERT, part of Carnegie Mellon University's Software Engineering Institute, to create socio-technical models of insider crime to help educate organizations on the risk of insider crime. Building upon this work, this paper seeks to demonstrate how a useful method for extracting technical information from previous insider crimes and mapping it to previous modeling work can create informed candidate technical controls and indicators. This paper also shows current examples of case material and candidate indicators that have een successfully converted into well-received insider threat training modules.
Source: Figshare
DOI: 10.1184/r1/22787867
Author: Hanley, Michael
Institution: Carnegie Mellon University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2114051155