Year: 2025
Type: conference-paper
Abstract: In this review, the significance of OSINT in contemporary cybersecurity is critically analysed, emphasizing the dual nature of OSINT in terms of being an effective instrument for threat identification and a latent liability in case of the alleged abuse.Our analysis examines the progression of OSINT methodologies, including the shift from raw manual data collection to the blending of AI-powered analytics for realtime intelligence acquisition.We highlight critical challenges, including how to handle an overwhelming amount of unstructured data, how to ensure that accurate data points are used without many erroneous data points, and how privacy and regulatory issues should be addressed.Furthermore, we found a lack of standardization in how data validation processes are handled in OSINT platforms, especially regarding the incorporation of fallback mechanisms.To mitigate these issues, we propose prevention strategies including rigorous quality assurance processes, robust encryption and secured access mechanisms, and autonomous, explainable AI models to map technical data to top-level threat intelligence.This review intends to create a holistic framework to facilitate the ethical and effective application of OSINT, with an eye towards more resilient cybersecurity in collectively informing research, policy, and practice in a rapidly digitalized world of October 2023.
Authors: Nitin Shrivas, Ajitabh Kalia, Ronit Roy, Sumit Sharma, Puneet Garg, Gaurav Agarwal
Language: English
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4411094322