Research by the method of an extended systematical literature review E-SLR the problem of ensuring the security of personal data when using OSINT

Objective. The amount of personal data in open sources increases, which makes it possible for third parties to access it using open source intelligence (OSINT) methods, which can be used for malicious purposes. The aim of the work is to identify threats and existing methods and means of ensuring the security of a user's personal data and his reputation when using OSINT by intruders, as well as to identify the main problems in protecting user PD taking into account OSINT. Method. The study uses an extended method of systematic literature review (e-SLR), which is a systematic literature review (SLR) supplemented by responses from ChatGPT, GigaCHAT, YndexGPT neural networks. Result. 41 sources were received for the analysis of the problem, on the basis of which threats to personal data were identified: violation of the confidentiality of personal data and the operation of information systems, targeted attacks using social engineering, password disclosure, espionage; protection tools: data processing before publication, anonymization and depersonalization, limitation of personal data, selection of sites, protection using OSINT, creation of complex passwords, use of protection tools, organizational measures; problems in the development of protection tools: working with big data, unreliability of information and sources, labor-intensiveness of data analysis, technical limitations, bias, ethical and legal aspects. Conclusion. The results were used to develop models for protecting personal data in open sources, methods and means for detecting and preventing violations of their security.