TY - GEN
T1 - Local Differential Privacy: Tools, Challenges, and Opportunities
AU - Ye, Qingqing
AU - Hu, Haibo
PY - 2020/1/19
Y1 - 2020/1/19
N2 - Local Differential Privacy (LDP), where each user perturbs her data locally before sending to an untrusted party, is a new and promising privacy-preserving model. Endorsed by both academia and industry, LDP provides strong and rigorous privacy guarantee for data collection and analysis. As such, it has been recently deployed in many real products by several major software and Internet companies, including Google, Apple and Microsoft in their mainstream products such as Chrome, iOS, and Windows 10. Besides industry, it has also attracted a lot of research attention from academia. This tutorial first introduces the rationale of LDP model behind these deployed systems to collect and analyze usage data privately, then surveys the current research landscape in LDP, and finally identifies several open problems and research directions in this community.
AB - Local Differential Privacy (LDP), where each user perturbs her data locally before sending to an untrusted party, is a new and promising privacy-preserving model. Endorsed by both academia and industry, LDP provides strong and rigorous privacy guarantee for data collection and analysis. As such, it has been recently deployed in many real products by several major software and Internet companies, including Google, Apple and Microsoft in their mainstream products such as Chrome, iOS, and Windows 10. Besides industry, it has also attracted a lot of research attention from academia. This tutorial first introduces the rationale of LDP model behind these deployed systems to collect and analyze usage data privately, then surveys the current research landscape in LDP, and finally identifies several open problems and research directions in this community.
KW - Data analysis
KW - Data collection
KW - Local differential privacy
UR - http://www.scopus.com/inward/record.url?scp=85080868079&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-3281-8_2
DO - 10.1007/978-981-15-3281-8_2
M3 - Conference article published in proceeding or book
AN - SCOPUS:85080868079
SN - 9789811532801
T3 - Communications in Computer and Information Science
SP - 13
EP - 23
BT - Web Information Systems Engineering - WISE 2019 Workshop, Demo, and Tutorial, Revised Selected Papers
A2 - U, Leong Hou
A2 - Yang, Jian
A2 - Cai, Yi
A2 - Karlapalem, Kamalakar
A2 - Liu, An
A2 - Huang, Xin
PB - Springer
T2 - 20th International Conference on Web Information Systems Engineering, WISE 2019 and on the International Workshop on Web Information Systems in the Era of AI, 2019
Y2 - 19 January 2020 through 22 January 2020
ER -