TRANSACTIONAL ANALYSIS FOR INSIDER THREAT DETECTION

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"'Insider Threat' is a formidable risk to business because it threatens both customer and employee trust. Accidental or malicious misuse of a firm's most sensitive and valuable data can result in customer identity theft, financial fraud, intellectual property theft, or damage to infrastructure. Because insiders have privileged access to data in order to do their jobs, it's usually difficult for security professionals to detect suspicious activity.The 2016 Forrester Report ""Hunting Insider Threats"" identified eight key factors as common motivators of Insider Threat: Financial distress; Employee disgruntlement; Perceived employee entitlement to sensitive information and IP; Job insecurity; Revenge; Conflict at work; Ideology and Outside influence.Our goal in this project is to use advanced AI and transactional analytics to (i) identify communication patterns characteristic of both team and company breakdown (hence identifying potential lack of engagement within teams and employees at risk of losing their job); (ii) identify language use characteristic of deception (alongside proven metrics of message \`sentiment'), enabling automatic alerts on potential employee distress, disgruntlement, insecurity etc. and (iii) identifying a-typical communication patterns to foreground signals characteristic of potential outside influence within a company."