ACM Home Page
Please provide us with feedback. Feedback
Anti-presistence: history independent data structures
Full text PdfPdf (308 KB)
Source Annual ACM Symposium on Theory of Computing archive
Proceedings of the thirty-third annual ACM symposium on Theory of computing table of contents
Hersonissos, Greece
Pages: 492 - 501  
Year of Publication: 2001
ISBN:1-58113-349-9
Authors
Moni Naor  Dept. of Computer Science and Applied Math, Weizmann Institute
Vanessa Teague  Dept. of Computer Science, Stanford University
Sponsor
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 6,   Downloads (12 Months): 34,   Citation Count: 5
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/10.1145/380752.380844
What is a DOI?

ABSTRACT

Many data structures give away much more information than they were intended to. Whenever privacy is important, we need to be concerned that it might be possible to infer information from the memory representation of a data structure that is not available through its “legitimate” interface. Word processors that quietly maintain old versions of a document are merely the most egregious example of a general problem.We deal with data structures whose current memory representation does not reveal their history. We focus on dictionaries, where this means revealing nothing about the order of insertions or deletions. Our first algorithm is a hash table based on open addressing, allowing O(1) insertion and search. We also present a history independent dynamic perfect hash table that uses space linear in the number of elements inserted and has expected amortized insertion and deletion time O(1). To solve the dynamic perfect hashing problem we devise a general scheme for history independent memory allocation. For fixed-size records this is quite efficient, with insertion and deletion both linear in the size of the record. Our variable-size record scheme is efficient enough for dynamic perfect hashing but not for general use. The main open problem we leave is whether it is possible to implement a variable-size record scheme with low overhead.


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
O. Amble and D. Knuth. Ordered hash tables. The Computer Journal, 17(2):135-142, 1974. Reprinted in: D. E. Knuth, Selected Papers on Analysis of Algorithms, Center for the Study of Language and Information Lecture Notes, no. 102, Stanford, 2000.
 
2
3
 
4
 
5
 
6
7
8
 
9
L. J. Guibas and E. Szemeredi. The analysis of double hashing. Journal of Computer and System Sciences, 16:226-274, 1978.
 
10
 
11
R. J. Lipton and J. F. Naughton. Clocked adversaries for hashing. Algorithmica, 9(3):239-252, 1993.
 
12
G. S. Lueker and M. Molodowitch. More analysis of double hashing. Combinatorica, 13(1):83-96, 1993.
13
14
 
15
R. Seidel and C. Aragon. Randomized search trees. Algorithmica, 16:464-497, 1996.
 
16
A. Siegel. On universal classes of fast high performance hash functions, their time-space tradeoff, and their applications. In Proc. 30th IEEE Symp. on Foundations of Computer Science, pages 20-25, 1989.
17
18


Collaborative Colleagues:
Moni Naor: colleagues
Vanessa Teague: colleagues