| LDR | | 01694nmm uu200385 4500 |
| 001 | | 000000333736 |
| 005 | | 20240805174437 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438376700 |
| 035 | |
▼a (MiAaPQ)AAI10824628 |
| 035 | |
▼a (MiAaPQ)duke:14759 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a He, Xi. |
| 245 | 10 |
▼a Policy Driven Data Sharing with Provable Privacy Guarantees. |
| 260 | |
▼a [S.l.] :
▼b Duke University.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 208 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B. |
| 500 | |
▼a Adviser: Ashwin Machanavajjhala. |
| 502 | 1 |
▼a Thesis (Ph.D.)--Duke University, 2018. |
| 520 | |
▼a Companies such as Google or Facebook collect a substantial amount of data about their users to provide useful services. The release of these datasets for general use can enable numerous innovative applications and scientific research. However, s |
| 520 | |
▼a This dissertation presents a novel policy-driven approach to design provable privacy guarantees for complex settings. This policy-driven approach results in a useful class of provable privacy definitions, named as Blowfish privacy, (a) generaliz |
| 590 | |
▼a School code: 0066. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a Duke University.
▼b Computer Science. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-02B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0066 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14998684
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자 |