An integrated framework for data breach on the dark web in brand monitoring data hunting

Siti Arpah Ahmad, Muhammad Al’Imran Mohd Khairuddin, Nor Shahniza Kamal Bashah, Nurul Aishah Ab Raman

Abstract


In today's digital landscape, data breaches pose a substantial threat, with the dark web serving as a prevalent platform for malevolent actors to perpetrate such incidents. Currently, security analysts use various tools to solve the problem, which is very time-consuming. This paper introduces a novel framework that integrates data breach monitoring within the dark web, focusing on brand monitoring and data hunting. The framework starts from the scraping process and continues with the utilisation of the Splunk dashboard. The dashboard provides an exhaustive overview of data breaches related to brands for both manual inquiries and rule-based detection mechanisms. The framework comprises five phases: data sourcing, data collection, integration, monitoring, and visualisation. The visualisation phase encompasses alert generation, notification mechanisms, and reporting functionalities. Moreover, the monitoring phase provides real-time surveillance, advanced search capabilities, brand monitoring, and threat intelligence integration. The integration phase involves security information and event management (SIEM) systems and security orchestration, automation, and response (SOAR) systems. This paper's result contributes to enhancing the National Institute of Standards and Technology (NIST) cybersecurity framework, offering a comprehensive solution to the data breaches challenge within the dark web and the frontiers of knowledge and security practices.

Keywords


Dark web; Data breach; Data safety; Personal identifiable information; Sensitive data

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DOI: http://doi.org/10.11591/ijece.v15i3.pp3162-3170

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International Journal of Electrical and Computer Engineering (IJECE)
p-ISSN 2088-8708, e-ISSN 2722-2578

This journal is published by the Institute of Advanced Engineering and Science (IAES).