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Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

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Analysing potential data security losses in organisations based on subsequent users logins.

Benjamin Aziz¹

¹School of Computing, University of Portsmouth, Portsmouth, United Kingdom.

|August 24, 2023

Summary

Shared computers risk data security. This study introduces subsequent user analysis to quantify data loss risk based on visibility and sensitivity, aiding secure login decisions in multi-user environments.

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Area of Science:

Cybersecurity
Information Security
Computer Science

Background:

Multi-user computer environments present data security risks from unauthorized subsequent users.
Locard's exchange principle highlights that digital traces can be exploited by others.
Existing security measures may not adequately address risks from sequential user access on shared systems.

Purpose of the Study:

To define and develop a subsequent user analysis framework.
To quantify potential data security loss in shared computing environments.
To provide a decision-making tool for users logging into shared computers.

Main Methods:

Developed a data-driven analysis based on data visibility and sensitivity values.
Defined metrics for calculating potential data security loss.
Validated the analysis using a large open Cybersecurity dataset linking users and computers.

Main Results:

The subsequent user analysis effectively calculates potential data security loss.
Demonstrated the practical applicability of the analysis in real-world scenarios.
The Cybersecurity dataset provided a robust foundation for analysis validation.

Conclusions:

Subsequent user analysis is a valuable tool for enhancing data security in shared environments.
Data visibility and sensitivity are key factors in assessing risk.
Informed decision-making regarding shared computer usage can be significantly improved.