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Efficient similarity search in sequence databases
, 1994
"... We propose an indexing method for time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT) to map time sequences to the frequency domain, the crucial observation being that, for most sequences of practical interest, only the first few frequencies are strong. Anot ..."
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Cited by 443 (21 self)
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We propose an indexing method for time sequences for processing similarity queries. We use the Discrete Fourier Transform (DFT) to map time sequences to the frequency domain, the crucial observation being that, for most sequences of practical interest, only the first few frequencies are strong. Another important observation is Parseval's theorem, which specifies that the Fourier transform preserves the Euclidean distance in the time or frequency domain. Having thus mapped sequences to a lowerdimensionality space by using only the first few Fourier coe cients, we use Rtrees to index the sequences and e ciently answer similarity queries. We provide experimental results which show that our method is superior to search based on sequential scanning. Our experiments show that a few coefficients (13) are adequate to provide good performance. The performance gain of our method increases with the number and length of sequences.
A PATTERN MATCHING MODEL FOR MISUSE INTRUSION DETECTION
"... This paper describes a generic model of matching that can be usefully applied to misuse intrusion detection. The model is based on Colored Petri Nets. Guards define the context in which signatures are matched. The notion of start and final states, and paths between them define the set of event seque ..."
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Cited by 166 (5 self)
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This paper describes a generic model of matching that can be usefully applied to misuse intrusion detection. The model is based on Colored Petri Nets. Guards define the context in which signatures are matched. The notion of start and final states, and paths between them define the set of event sequences matched by the net. Partial order matching can also be specified in this model. The main benefits of the model are its generality, portability and flexibility.
An Application of Pattern Matching in Intrusion Detection
, 1994
"... This report examines and classifies the characteristics of signatures used in misuse intrusion detection. Efficient algorithms to match patterns in some of these classes are described. A generalized model for matching intrusion signatures based on Colored Petri Nets is presented, and some of its pro ..."
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Cited by 76 (5 self)
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This report examines and classifies the characteristics of signatures used in misuse intrusion detection. Efficient algorithms to match patterns in some of these classes are described. A generalized model for matching intrusion signatures based on Colored Petri Nets is presented, and some of its properties are derived.
From Personal Computer to Personal Assistant
"... Abstract: Much oftheconfusion that surrounds electronic personal assistants arises from the openended complexity oftheir development. In this paper we categorise some of their more common uses before suggesting several thoughtprovoking extensions. ..."
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Cited by 1 (0 self)
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Abstract: Much oftheconfusion that surrounds electronic personal assistants arises from the openended complexity oftheir development. In this paper we categorise some of their more common uses before suggesting several thoughtprovoking extensions.
An Algorithm for Estimating all Matches Between Two Strings
"... We give a randomized algorithm for estimating the score vector of matches between a text string of length N and a pattern string of length M; this is the vector obtained when the pattern is slid along the text, and the number of matches is counted for each position. The randomized algorithm takes de ..."
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We give a randomized algorithm for estimating the score vector of matches between a text string of length N and a pattern string of length M; this is the vector obtained when the pattern is slid along the text, and the number of matches is counted for each position. The randomized algorithm takes deterministic time O((N=M)Conv(M)) where Conv(M) is the time for performing a convolution of two vectors of size M each. The algorithm nds an unbiased estimator of the scores, whose variance is particularly small for scores that are close to M, i.e., for approximate occurrences of the pattern in the text. No assumptions are made about the probabilistic characteristics of the input, or about the number of di erent symbols appearing in T or P (i.e., the alphabet size need not be much smaller than M). The solution extends to the weighted case and to higher dimensions.
Agrep  A Fast Approximate PatternMatching Tool
, 2006
"... Searching for a pattern in a text file is a very common operation in many applications ranging from text editor sand databases to applications in molecular biology. In many instances the pattern does not appear in the text exactly. Errors in the text or in the query can result from misspelling or f ..."
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Searching for a pattern in a text file is a very common operation in many applications ranging from text editor sand databases to applications in molecular biology. In many instances the pattern does not appear in the text exactly. Errors in the text or in the query can result from misspelling or from experimental errors (e.g., when the text is a DNA sequence). The use of such approximate pattern matching has been limited until now to specific applications. Most text editors and searching programs do not support searching with errors because of the complexity involved in implementing it. In this paper we describe a new tool, called agrep, for approximatepattern matching. Agrep is based on a new efficient and flexible algorithm for approximate string matching. Agrep is also competitive with other tools for exact string matching; it include many options that make searching more powerful and convenient.