Preventing data leakage: A risk based approach for controlled use of the use of administrative and access privileges

Organizations invest resources to protect their confidential information and intellectual property by trying to prevent data leakage or data loss. They adopt policies and implement technical controls to stop the loss and disclosure of sensitive information by outside attackers as well as inadvertent and malicious insiders. They follow best practices like the Critical Security Controls, specifically Control 12 (Controlled Use of Administrative Privileges) and Control 17 (Data Protection), to prevent the unauthorized leakage and disclosure of sensitive information. One type of data loss or data leakage prevention controls includes endpoint protection solutions to stop file transfers to USB storage devices or file uploads to public websites. However, the larger and more complex the business and organization the more users that may be granted exceptions to these policies and controls in order for them to be able to fulfill their job related tasks. The approval of these exceptions is often solely based on the business need for the individual user. This raises the question of how an approval for an exception does influence the risk of data leakage for an organization? What is the specific data leakage risk for granting an individual user a certain exception? This paper presents a new approach to risk based exception management, which will allow organizations to grant exceptions based on inherent data leakage risk. First, this paper introduces a concept for evaluating and categorizing users based on their access to sensitive information. Then in the second step, a ruleset is defined for granting exceptions based on the categorization of users, which enables individual approvers to make informed decisions regarding exception requests. The overall objective is to lower the data leakage risk for organizations by controlling and limiting exceptions where the access and thereby potential loss of information is the highest.