Protect Against Unintentional Insider Threats: The risk of an employee's cyber misconduct on a Social Media Site

TL;DR

This paper investigates how employee behavior on social media, especially LinkedIn, can pose cybersecurity risks to organizations by analyzing data leakage and personality traits to predict tendencies toward disclosing sensitive information.

Contribution

It introduces a novel approach to analyzing open-source social media data to identify behavioral factors linked to unintentional insider threats in cybersecurity.

Findings

Identification of behavioral patterns associated with data leakage

Analysis of personality types related to disclosing sensitive data

Development of a predictive model for insider threat tendencies

Abstract

Social Media is a cyber-security risk for every business. What do people share on the Internet? Almost everything about oneself is shared: friendship, demographics, family, activities, and work-related information. This could become a potential risk in every business if the organization's policies, training and technology fail to properly address these issues. In many cases, it is the employees' behaviour that can put key company information at danger. Social media has turned into a reconnaissance tool for malicious actors and users accounts are now seen as a goldmine for cyber criminals. Investigation of Social Media is in the embryonic stage and thus, is not yet well understood. This research project aims to collect and analyse open-source data from LinkedIn, discover data leakage and analyse personality types through software as a service (SAAS). The final aim of the study is to understand if there are behavioral factors that can predicting one's attitude toward disclosing sensitive data.