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This paper defines a methodology for extracting unique objects representing users or devices from heterogeneous digital evidence during digital investigations, specifically in the context of IoT forensics. It focuses on the challenges of data correlation and normalization, proposing the JUDAS tool to visually illustrate the relationships through dynamic graphs, validated with data extracted from Amazon\'s Alexa Cloud.
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Identify the objective of becoming Judas correlating users.
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Gather data on user interactions and behaviors.
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Becoming Judas correlating users refers to a process or system that aligns or connects users who share similar traits or behaviors, often in a digital context, enabling data analysis or other applications.
Individuals or organizations that are engaged in activities that involve user correlation data or related analytics are typically required to file becoming Judas correlating users.
To fill out becoming Judas correlating users, individuals or organizations must provide the required user information, correlation data, and any additional details as specified in the filing guidelines.
The purpose of becoming Judas correlating users is to analyze and leverage user data for insights that may enhance user experience, improve services, or fulfill regulatory requirements.
The information that must be reported typically includes user identifiers, correlation metrics, data sources, and any related analytics outcomes that are relevant to the correlation process.
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