The Impact of Digital Fingerprint Evolution on the Authenticity of Anonymous User Identification

Abstract

Purpose of work – is to evaluate the effectiveness of software identification of anonymous users in the context of the evolution of digital fingerprints on their devices. Research method. Artificial intelligence technologies, including NLP (Natural Language Processing), methods of LSA (Latent semantic analysis), as well as methods of clustering and machine learning. Objects of study are theoretical and practical issues of solving and visualizing information security problems. Results of the study. To study the impact of the evolution of digital fingerprints of analyzed devices, by alternately changing the analyzed parameters of the original fingerprint (a digital fingerprint of a browser or digital device), a database of modified fingerprints was created. A calculation technique is proposed and numerical results are presented for estimating the probability of correct and false user identifications during the evolution of the attributes of digital fingerprints. The dependence of the effectiveness of user deanonymization depending on the characteristics and properties of the variable attributes of digital fingerprints of his devices is shown. Practical relevance relevance. To improve the efficiency of anonymous user identification systems based on the analysis of device digital fingerprints. The proposed article will be useful both to specialists developing information security systems and to students studying “Information Security” course.