תקציר
Data mining is a highly productive tool, while also a source for privacy violation. Privacy has become one of the most significant concerns in the digital era, mainly due to the information disclosure enabled by data mining. Privacy-preserving data mining (PPDM) is a collection of methodologies aimed to minimize and control the amount of private information disclosure in data mining processes. I present the various approaches to achieve PPDM: anonymization, randomization, cryptography, and privatizing results as well as various common methodologies and techniques used to implement these approaches.
שפה מקורית | אנגלית |
---|---|
כותר פרסום המארח | Machine Learning for Data Science Handbook |
כותר משנה של פרסום המארח | Data Mining and Knowledge Discovery Handbook, Third Edition |
עמודים | 887-911 |
מספר עמודים | 25 |
מסת"ב (אלקטרוני) | 9783031246289 |
מזהי עצם דיגיטלי (DOIs) | |
סטטוס פרסום | פורסם - 1 ינו׳ 2023 |