Reducing Insider Risk Through Positive Deterrence

Abstract

Most organizations approach insider risk management with a command-and-control focus, pressuring employees to act in the interests of the organization through external controls. Positive deterrence complements the command-and-control approach by aligning and reinforcing the mutual interests of the individual and the organization in ways that further reduce insider risk. This brief report describes why and how insider risk management programs should consider augmenting their command-and-control strategies with positive deterrence. Programs that embrace positive deterrence can unlock greater potential to minimize insider risk and employees negative perception of the command-and-control approach. We provide actionable guidance on how organizations can combine positive deterrence and command-and-control of insider threat in a balanced way to take advantage of the reduced insider risk that it affords. As a complement to command-and-control, positive deterrence creates a work environment that reinforces the bond between the organization and its workforce, contributing to the well-being of both.

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Document Details

Document Type
Technical Report
Publication Date
Aug 02, 2022
Accession Number
AD1181298

Entities

People

  • Andrew P. Moore
  • Carrie Gardner
  • Denise M. Rousseau

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Biomedical
  • Cyber

DTIC Thesaurus Topics

  • Applied Psychology
  • Business Administration
  • Command And Control
  • Deterrence
  • Employment
  • Engineering
  • Human Resources
  • Identification
  • Insider Threats
  • Job Satisfaction
  • Management Personnel
  • Organizational Structure
  • Perception
  • Personnel Management
  • Psychology
  • Risk Management
  • Security
  • Social Psychology
  • Software Development

Readers

  • Cybersecurity.
  • Organizational Psychology.
  • Strategic Security Studies

Technology Areas

  • Fully Networked C3
  • Fully Networked C3 - Command and Control