Integration of GenAI and Behavioral Analysis in an Authentication System
DOI:
https://doi.org/10.70862/CSIR.2025.0202-17Keywords:
generative artificial intelligence , GenAI, behavioral security, reactive architecture, anomaly detection, authenticationAbstract
This paper presents a model of a security-enhanced web authentication system that combines behavioral analysis, generative artificial intelligence, and an event-driven architecture. The aim of the study is to develop a dynamic monitoring and alerting mechanism capable of identifying unusual activity based on contextual and behavioral indicators, without imposing additional authentication steps on the user. The system leverages Redis with Pub/Sub and TTL notifications for reactive event processing, generative AI for automatic summarization of logs into a human-readable format, and the Isolation Forest algorithm for experimental detection of behavioral anomalies. The results demonstrate that the proposed architecture can effectively identify suspicious sessions, provide interpretable textual explanations of user actions, and react to key events in real time while maintaining low latency.
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Copyright (c) 2025 Georgi Atanasov, Kostadin Yotov, Emil Hadzhikolev (Author)
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