ACM Home Page
Please provide us with feedback. Feedback
Private approximation of search problems
Full text PdfPdf (203 KB)
Source Annual ACM Symposium on Theory of Computing archive
Proceedings of the thirty-eighth annual ACM symposium on Theory of computing table of contents
Seattle, WA, USA
SESSION: Session 2B table of contents
Pages: 119 - 128  
Year of Publication: 2006
ISBN:1-59593-134-1
Authors
Amos Beimel  Ben-Gurion University, Beer-Sheva, Israel
Paz Carmi  Ben-Gurion University, Beer-Sheva, Israel
Kobbi Nissim  Ben-Gurion University, Beer-Sheva, Israel
Enav Weinreb  Ben-Gurion University, Beer-Sheva, Israel
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 7,   Downloads (12 Months): 34,   Citation Count: 2
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1132516.1132533
What is a DOI?

ABSTRACT

Many approximation algorithms have been presented in the last decades for hard search problems. The focus of this paper is on cryptographic applications, where it is desired to design algorithms which do not leak unnecessary information. Specifically, we are interested in private approximation algorithms -- efficient algorithms whose output does not leak information not implied by the optimal solutions to the search problems. Privacy requirements add constraints on the approximation algorithms; in particular, known approximation algorithms usually leak a lot of information.For functions, [Feigenbaum et al., ICALP 2001] presented a natural requirement that a private algorithm should not leak information not implied by the original function. Generalizing this requirement to search problems is not straightforward as an input may have many different outputs. We present a new definition that captures a minimal privacy requirement from such algorithms -- applied to an input instance, it should not leak any information that is not implied by its collection of exact solutions. Although our privacy requirement seems minimal, we show that for well studied problems, as vertex cover and 3SAT, private approximation algorithms are unlikely to exist even for poor approximation ratios. Similar to [Halevi et al., STOC 2001], we define a relaxed notion of approximation algorithms that leak (little) information, and demonstrate the applicability of this notion by showing near optimal approximation algorithms for 3SAT that leak little information.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
N. Alon, O. Goldreich, J. Hastad, and R. Peralta. Simple constructions of almost k-wise independent random variables. Random Structures & Alg., 3:289--304, 1992.
 
3
R. Bar-Yehuda, B. Chor, E. Kushilevitz, and A. Orlitsky. Privacy, additional information, and communication. IEEE Trans. on Information Theory, 39(6):1930--1943, 1993.
 
4
R. Bar-Yehuda and S. Even. A local-ratio theorem for approximating the weighted vertex cover problem. Annals of Disc. Math., 25:27--46, 1985.
 
5
A. Beimel, P. Carmi, K. Nissim, and E. Weinreb. Private approximation of search problems. Technical Report TR05-141, ECCC, 2005.
6
 
7
B. Chor, J. Friedmann, O. Goldreich, J. Hastad, S. Rudich, and R. Smolansky. The bit extraction problem or t-resilient functions. In the 26th FOCS, pages 396--407, 1985.
 
8
I. Dinur and S. Safra. On the hardness of approximating minimum vertex cover. Annals of Math., 162(1), 2005.
 
9
 
10
M. J. Freedman, K. Nissim, and B. Pinkas. Efficient private matching and set intersection. In EUROCRYPT 2004, volume 3027 of LNCS, pages 1--19, 2004.
11
 
12
 
13
 
14
15
 
16
17
 
18
P. Indyk and D. Woodruff. Polylogarithmic private approximations and efficient matching. TCC 2006, volume 3876 of LNCS, pages 245--264, 2006.
 
19
D. S. Johnson. Approximation algorithms for combinatorial problems. JCSS, 9:256--278, 1974.
 
20
E. Kiltz, G. Leander, and J. Malone-Lee. Secure computation of the mean and related statistics. In TCC 2005, volume 3378 of LNCS, pages 283--302, 2005.
 
21
 
22
 
23
 
24
 
25
E. Petrank and G. Tardos. On the knowledge complexity of NP. Combinatorica, 22(1):83--121, 2002.
 
26
A. C. Yao. Protocols for secure computations. In the 23th FOCS, pages 160--164, 1982.


Collaborative Colleagues:
Amos Beimel: colleagues
Paz Carmi: colleagues
Kobbi Nissim: colleagues
Enav Weinreb: colleagues