Fast text anonymization using k-anonyminity

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Internal and External Threat Analysis of Anonymized Dataset

Jindal

Saini

2020

Handbook of Research on Intrusion Detection Systems

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In recent years, data collection and data mining have emerged as fast-paced computational processes as the amount of data from different sources has increased manifold. With the advent of such technologies, major concern is exposure of an individual's self-contained information. To confront the unusual situation, anonymization of dataset is performed before being released into public for further usage. The chapter discusses various existing techniques of anonymization. Thereafter, a novel redaction technique is proposed for generalization to minimize the overall cost (penalty) of the process being inversely proportional to utility of generated dataset. To validate the proposed work, authors assume a pre-processed dataset and further compare our algorithm with existing techniques. Lastly, the proposed technique is made scalable thus ensuring further minimization of generalization cost and improving overall utility of information gain.

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Fast text anonymization using k-anonyminity

Cited by 3 publications

References 9 publications

A k-anonymized Text Generation Method

A k-anonymized Text Generation Method

Privacy-Preserving Data Publishing

Internal and External Threat Analysis of Anonymized Dataset

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