A survey deriving private information from perturbed data
Yazarlar (4)
Dr. Öğr. Üyesi Burcu DEMİRELLİ OKKALIOĞLU Yalova Üniversitesi, Türkiye
Doç. Dr. Murat OKKALIOĞLU Yalova Üniversitesi, Türkiye
Dr. Öğr. Üyesi Mehmet Koc Bilecik Şeyh Edebali Üniversitesi, Türkiye
Dr. Öğr. Üyesi Huseyin Polat Anadolu Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Artificial Intelligence Review (Q2) | ||
| Dergi ISSN | 0269-2821 Dergi Bilgileri (2015) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | İngilizce | Basım Tarihi | 12-2015 |
| Cilt / Sayı / Sayfa | 44 / 4 / 547–569 | DOI | 10.1007/s10462-015-9439-5 |
| Makale Linki | http://link.springer.com/10.1007/s10462-015-9439-5 | ||
| UAK Araştırma Alanları |
Bilgisayar Bilimleri ve Mühendisliği
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| Özet |
| Privacy-preserving data mining has attracted the attention of a large number of researchers. Many data perturbation methods have been proposed to ensure individual privacy. Such methods seem to be successful in providing privacy and accuracy. On one hand, different methods are utilized to preserve privacy. On the other hand, various data reconstruction approaches have been proposed to derive private information from perturbed data. Thus, many researchers have been conducting various studies about data reconstruction methods and the resilience of data perturbation schemes. In this survey, we focus on data reconstruction methods due to their importance in privacy-preserving data mining. We provide a detailed review of the data reconstruction methods and the data perturbation schemes attacked by different data reconstruction techniques. We merge our review with the evaluation metrics and the data … |
| Anahtar Kelimeler |
| Attack resilience | Data perturbation | Data reconstruction | Privacy | Spectral filtering |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Yöksis | 3 |
| Web of Science | 22 |
| Scopus | 33 |
| Google Scholar | 46 |