A psychometric approach to email authorship assertion in an organization

Abstract

Email services have become an integral aspect of modern communication. Emails can be transmitted digitally without the adequate authentication of the sender. As a result, there has been a considerable surge in security threats coming from email communication, such as phishing, spear phishing, whaling, and malware deposition through emails where recipients can be duped into acting. Authorship assertion of the sender can prevent several security issues, particularly in an organizational setting where an employee’s trust can be compromised by faking an email from a colleague or senior without exposing any specific system weakness. A psychometric approach to determining the authorship of an email in an organization is proposed in this research. Machine learning (ML) models have been developed using four classification algorithms. The performance of these ML models has been compared.