Global ETD Search
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Showing 1 to 2 of 2 for “"Graph Anonymization"”.
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Empirical Evaluation of Graph-Anonymized Metrics for JIT Defect Prediction
… data privacy. To address these challenges, anonymization techniques like MORPH, LACE, and LACE2 provide privacy to defect prediction data. While effective, they often sacrifice metric performance due to a disregard for data relationships during anonymization. To preserve these relationships, …
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Learning to de-anonymize social networks
… Despite evidence to the contrary the belief that anonymization will solve the privacy problem in practice refuses to die. This dissertation contributes to the field of social graph de-anonymization by demonstrating that even automated models can be quite successful in breaching the privacy of such …