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Approximate TwoParty PrivacyPreserving String Matching with Linear Complexity
"... Abstract—Consider two parties who want to compare their strings, e.g., genomes, but do not want to reveal them to each other. We present a system for privacypreserving matching of strings, which differs from existing systems by providing a deterministic approximation instead of an exact distance. I ..."
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Abstract—Consider two parties who want to compare their strings, e.g., genomes, but do not want to reveal them to each other. We present a system for privacypreserving matching of strings, which differs from existing systems by providing a deterministic approximation instead of an exact distance
An Iterative TwoParty Protocol for Scalable PrivacyPreserving Record Linkage
"... Record linkage is the process of identifying which records in different databases refer to the same realworld entities. When personal details of individuals, such as names and addresses, are used to link databases across different organisations, then privacy becomes a major concern. Often it is not ..."
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infer anysensitiveinformationabouttheotherparty’sdata during the linkage process. Our twoparty protocol uses an efficient privacy technique called Bloom filters, and conducts an iterative classification of record pairs into matches and nonmatches, as selected bits of the Bloom filters are revealed
Tries for Approximate String Matching
 IEEE Transactions on Knowledge and Data Engineering
, 1996
"... Tries offer text searches with costs which are independent of the size of the document being searched, and so are important for large documents requiring spelling checkers), case insensitivity, and limited approximate regular secondary storage. Approximate searches, in which the search pattern d ..."
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Cited by 34 (1 self)
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Tries offer text searches with costs which are independent of the size of the document being searched, and so are important for large documents requiring spelling checkers), case insensitivity, and limited approximate regular secondary storage. Approximate searches, in which the search pattern
Formal Analysis of a PrivacyPreserving Billing Protocol
"... Abstract. We provide a formal model and a security analysis of the Private Billing Protocol. This formal analysis allowed us to spell out precisely the details of the protocol, the security assumptions as well as the expected security goals. For the formal analysis we used SATMC, a model checker for ..."
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for security protocol analysis that supports the specification of security assumptions and goals as LTL formulae. Further analysis that we conducted manually revealed that the protocol allows for implementations that fail to meet the expected privacy goal. We describe the implications of our findings
On the Size of Minimal Automata for Approximate String Matching
, 1997
"... A natural way to solve the problem of string matching with k mismatches, is to construct a finite automaton recognizing the language LP;k of all strings being at a distance k of the searched pattern P , and to use it for a linear search in the text. The problem of this approach is a high space compl ..."
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A natural way to solve the problem of string matching with k mismatches, is to construct a finite automaton recognizing the language LP;k of all strings being at a distance k of the searched pattern P , and to use it for a linear search in the text. The problem of this approach is a high space
A Unified View to String Matching Algorithms
 IN PROC. THEORY AND PRACTICE OF INFORMATICS (SOFSEM'96), LNCS 1175
, 1996
"... We present a unified view to sequential algorithms for many pattern matching problems, using a finite automaton built from the pattern which uses the text as input. We show the limitations of deterministic finite automata (DFA) and the advantages of using a bitwise simulation of nondeterminis ..."
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Cited by 14 (3 self)
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deterministic finite automata (NFA). This approach gives very fast practical algorithms which have good complexity for small patterns on a RAM machine with word length O(log n), where n is the size of the text. For generalized string matching the time complexity is O(mn= log n) which for small patterns is linear
String matching with inversions and translocations in linear average time (most of the time
 Inf. Process. Lett
"... Abstract. We present an efficient algorithm for finding all approximate occurrences of a given pattern p of length m in a text t of length n allowing for translocations of equal length adjacent factors and inversions of factors. The algorithm is based on an efficient filtering method and has an O(n ..."
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Abstract. We present an efficient algorithm for finding all approximate occurrences of a given pattern p of length m in a text t of length n allowing for translocations of equal length adjacent factors and inversions of factors. The algorithm is based on an efficient filtering method and has an O
Weighted Finite Automata in Hardware for Approximate Pattern Matching
"... String processing. String processing over large databases plays a key role in some applications. Biologists, for example, frequently compare new sequences with known ones in genomic databases. Good software solutions are provided by indexing techniques, which must preprocess data (in linear time at ..."
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at the fastest) then process queries in O(1) time. Those solutions are very effective for exact pattern matching, but some complex matchings require complete scanning of whole databases at each run. Dedicated hardware can then provide a speedup for this type of queries. Approximative pattern matching. Given a
Polylogarithmic Approximation for Edit Distance and the Asymmetric Query Complexity
, 2010
"... We present a nearlinear time algorithm that approximates the edit distance between two strings within a polylogarithmic factor; specifically, for strings of length n and every fixed ε> 0, it can compute a (log n) O(1/ε) approximation in n 1+ε time. This is an exponential improvement over the pre ..."
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Cited by 6 (2 self)
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We present a nearlinear time algorithm that approximates the edit distance between two strings within a polylogarithmic factor; specifically, for strings of length n and every fixed ε> 0, it can compute a (log n) O(1/ε) approximation in n 1+ε time. This is an exponential improvement over
Beating O(nm) in approximate LZWcompressed pattern matching
"... Abstract. Given an LZW/LZ78 compressed text, we want to find an approximate occurrence of a given pattern of length m. The goal is to achieve time complexity depending on the size n of the compressed representation of the text instead of its length. We consider two specific definitions of approxima ..."
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Abstract. Given an LZW/LZ78 compressed text, we want to find an approximate occurrence of a given pattern of length m. The goal is to achieve time complexity depending on the size n of the compressed representation of the text instead of its length. We consider two specific definitions
Results 1  10
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