Entropy-Based Correlation Analysis for Privacy Risk Assessment in IoT Identity Ecosystem
As the Internet of Things (IoT) expands, robust tools for assessing privacy risk are increasingly critical. This research introduces a quantitative framework for evaluating IoT privacy risks, centered on two algorithmically derived scores: the Personalized Privacy Assistant (PPA) score and the Priva...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-07-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/27/7/723 |
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| _version_ | 1839616021015560192 |
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| author | Kai-Chih Chang Suzanne Barber |
| author_facet | Kai-Chih Chang Suzanne Barber |
| author_sort | Kai-Chih Chang |
| collection | DOAJ |
| description | As the Internet of Things (IoT) expands, robust tools for assessing privacy risk are increasingly critical. This research introduces a quantitative framework for evaluating IoT privacy risks, centered on two algorithmically derived scores: the Personalized Privacy Assistant (PPA) score and the PrivacyCheck score, both developed by the Center for Identity at The University of Texas. We analyze the correlation between these scores across multiple types of sensitive data—including email, social security numbers, and location—to understand their effectiveness in detecting privacy vulnerabilities. Our approach leverages Bayesian networks with cycle decomposition to capture complex dependencies among risk factors and applies entropy-based metrics to quantify informational uncertainty in privacy assessments. Experimental results highlight the strengths and limitations of each tool and demonstrate the value of combining data-driven risk scoring, information-theoretic analysis, and network modeling for privacy evaluation in IoT environments. |
| format | Article |
| id | doaj-art-426db85de9db4b068bac0c4be83c81ef |
| institution | Matheson Library |
| issn | 1099-4300 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj-art-426db85de9db4b068bac0c4be83c81ef2025-07-25T13:22:20ZengMDPI AGEntropy1099-43002025-07-0127772310.3390/e27070723Entropy-Based Correlation Analysis for Privacy Risk Assessment in IoT Identity EcosystemKai-Chih Chang0Suzanne Barber1Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USADepartment of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX 78712, USAAs the Internet of Things (IoT) expands, robust tools for assessing privacy risk are increasingly critical. This research introduces a quantitative framework for evaluating IoT privacy risks, centered on two algorithmically derived scores: the Personalized Privacy Assistant (PPA) score and the PrivacyCheck score, both developed by the Center for Identity at The University of Texas. We analyze the correlation between these scores across multiple types of sensitive data—including email, social security numbers, and location—to understand their effectiveness in detecting privacy vulnerabilities. Our approach leverages Bayesian networks with cycle decomposition to capture complex dependencies among risk factors and applies entropy-based metrics to quantify informational uncertainty in privacy assessments. Experimental results highlight the strengths and limitations of each tool and demonstrate the value of combining data-driven risk scoring, information-theoretic analysis, and network modeling for privacy evaluation in IoT environments.https://www.mdpi.com/1099-4300/27/7/723identityprivacyprivacy policyInternet of Thingsprivacy risksentropy |
| spellingShingle | Kai-Chih Chang Suzanne Barber Entropy-Based Correlation Analysis for Privacy Risk Assessment in IoT Identity Ecosystem Entropy identity privacy privacy policy Internet of Things privacy risks entropy |
| title | Entropy-Based Correlation Analysis for Privacy Risk Assessment in IoT Identity Ecosystem |
| title_full | Entropy-Based Correlation Analysis for Privacy Risk Assessment in IoT Identity Ecosystem |
| title_fullStr | Entropy-Based Correlation Analysis for Privacy Risk Assessment in IoT Identity Ecosystem |
| title_full_unstemmed | Entropy-Based Correlation Analysis for Privacy Risk Assessment in IoT Identity Ecosystem |
| title_short | Entropy-Based Correlation Analysis for Privacy Risk Assessment in IoT Identity Ecosystem |
| title_sort | entropy based correlation analysis for privacy risk assessment in iot identity ecosystem |
| topic | identity privacy privacy policy Internet of Things privacy risks entropy |
| url | https://www.mdpi.com/1099-4300/27/7/723 |
| work_keys_str_mv | AT kaichihchang entropybasedcorrelationanalysisforprivacyriskassessmentiniotidentityecosystem AT suzannebarber entropybasedcorrelationanalysisforprivacyriskassessmentiniotidentityecosystem |