MODEL OF INFORMATION ATTACK ON ENTERPRISES USING FAKE DIGITAL IDENTITIES

Abstract

The article discusses a new type of cyber threats related to the use of deepfake technologies to create fake digital identities in the context of targeted attacks on financial, corporate and governmental entities. The purpose of the study is to build a formalized model of an information attack, including the stages of collecting media data, setting up a fake digital infrastructure, establishing trust with target employees, and implementing malicious requests.

The research methodology is based on the analysis of incidents recorded in open sources using The MIT AI Risk Repository taxonomy. As a result, it was found that the main targets of impersonation are top managers, and the attacks themselves are mostly aimed at employees with access to financial resources. The article also contains recommendations for proactive digital identity protection, including the use of watermarks, multi-level verification, and mechanisms such as D-CAPTCHA. The presented results can be used to improve cybersecurity strategies in the face of the growing threat from generative artificial intelligence technologies.