Artificial Intelligence in Data Analysis for Open-Source Investigations

Abstract

The developed OSINT platform organizes data hierarchically and integrates a GPT model for faster, easier large data processing. Users can interact with the GPT model through natural language communication with a virtual agent for data processing commands. Open source investigations face challenges like vast data volumes and incorrect information. To address these issues, a real-time data processing tool is needed. Our OSINT platform integrates a GPT model trained to learn from data, enhancing the efficiency of open source investigations. We assessed various natural language processing models, focusing on the benefits of pretraining, fine-tuning., and generative models in open source investigations. GPT models excel due to pretraining on extensive text data, allowing fine-tuning for specific tasks and domains., giving investigators a robust tool for text analysis. The generative nature of GPT models benefits OSINT investigations by producing human-like text for extracting insights and identifying patterns. Fine-tuning enables customization to specific domains or topics., increasing accuracy and reliability while reducing time and effort in data analysis. In conclusion., our OSINT platform presents an innovative solution for open source investigations by incorporating a GPT model for efficient information processing. The Davinci model by OpenAI outperforms other evaluated models., enhancing investigation efficiency and maintaining grammatical accuracy. This work highlights the significance of natural language processing models in open source investigations and paves the way for future research.