Challenges of Privacy-Preserving OLAP Techniques

被引:0
|
作者
Gorlatykh, Andrey V. [1 ]
Zapechnikov, Sergey V. [1 ]
机构
[1] Natl Res Nucl Univ MEPhI, Moscow Engn Phys Inst, Dept Cryptol & Cybersecur, Moscow, Russia
关键词
On-line Analytical Processing (OLAP); information security; privacy; partly homomorphic encryption;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Over the last five years, on-line analytical processing (OLAP) became one of the essential information processing technologies. OLAP technology has been successfully used in different areas: retail, financial services, telecommunication, health care etc. Because of this security of data stored in Data Warehouses became one of the most important aspect of this technology, especially when we speaking about data privacy. We review existing privacy-preserving OLAP techniques and identify new challenges of this technology. In particular, OLAP databases are placed often in the untrusted clouds, so it is crucial to create techniques for evaluating widely used statistical functions (mean value, standard deviation, minimum, maximum, and so on) over the encrypted data. For this purpose, we review and compare encryption schemes with special features (partly homomorphic, order-preserving, deterministic etc.) and suggest architecture of application for private OLAP over the encrypted database.
引用
收藏
页码:404 / 408
页数:5
相关论文
共 50 条
  • [31] Empowering federated learning techniques for privacy-preserving PV
    Michalakopoulos, Vasilis
    Sarantinopoulos, Efstathios
    Sarmas, Elissaios
    Marinakis, Vangelis
    ENERGY REPORTS, 2024, 12 : 2244 - 2256
  • [32] Privacy-Preserving Techniques in Cloud/Fog and Internet of Things
    Lee, Cheng-Chi
    Gheisari, Mehdi
    Shayegan, Mohammad Javad
    Ahvanooey, Milad Taleby
    Liu, Yang
    CRYPTOGRAPHY, 2023, 7 (04)
  • [33] A survey on genomic data by privacy-preserving techniques perspective
    Abinaya, B.
    Santhi, S.
    COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2021, 93
  • [34] Suppression techniques for privacy-preserving trajectory data publishing
    Lin, Chen-Yi
    KNOWLEDGE-BASED SYSTEMS, 2020, 206
  • [35] Privacy-preserving artificial intelligence in healthcare: Techniques and applications
    Khalid, Nazish
    Qayyum, Adnan
    Bilal, Muhammad
    Al-Fuqaha, Ala
    Qadir, Junaid
    COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 158
  • [36] Privacy-Preserving OLAP via Modeling and Analysis of Query Workloads: Innovative Theories and Theorems
    Cuzzocrea, Alfredo
    35TH INTERNATIONAL CONFERENCE ON SCIENTIFIC AND STATISTICAL DATABASE MANAGEMENT, SSDBM 2023, 2023,
  • [37] An efficient privacy preserving method in OLAP
    Key Laboratory of Machine Perception, Peking University, Beijing 100871, China
    Beijing Daxue Xuebao Ziran Kexue Ban, 2008, 5 (705-710):
  • [38] FMC: An approach for privacy preserving OLAP
    Hua, M
    Zhang, SZ
    Wang, W
    Zhou, HF
    Shi, BL
    DATA WAREHOUSING AND KNOWLEDGE DISCOVERY, PROCEEDINGS, 2005, 3589 : 408 - 417
  • [39] Privacy-preserving boosting
    Sébastien Gambs
    Balázs Kégl
    Esma Aïmeur
    Data Mining and Knowledge Discovery, 2007, 14 : 131 - 170
  • [40] Privacy-preserving boosting
    Gambs, Sebastien
    Kegl, Balazs
    Aimeur, Esma
    DATA MINING AND KNOWLEDGE DISCOVERY, 2007, 14 (01) : 131 - 170