• Title/Summary/Keyword: increasing subsequences

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Mining Regular Expression Rules based on q-grams

  • Lee, Inbok
    • Smart Media Journal
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    • v.8 no.3
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    • pp.17-22
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    • 2019
  • Signature-based intrusion systems use intrusion detection rules for detecting intrusion. However, writing intrusion detection rules is difficult and requires considerable knowledge of various fields. Attackers may modify previous attempts to escape intrusion detection rules. In this paper, we deal with the problem of detecting modified attacks based on previous intrusion detection rules. We show a simple method of reporting approximate occurrences of at least one of the network intrusion detection rules, based on q-grams and the longest increasing subsequences. Experimental results showed that our approach could detect modified attacks, modeled with edit operations.

Linear-time algorithms for computing a maximal increasing subsequence (극대 증가 부분서열을 찾는 선형 알고리즘)

  • Joong Chae Na
    • Smart Media Journal
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    • v.12 no.6
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    • pp.9-14
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    • 2023
  • The longest increasing subsequence is a fundamental problem which has been studied for a long time in computer science. In this paper, we consider the maximal increasing subsequence problem where the constraint is released from the longest to the maximal. For two kinds of increasing (monotone increasing and strictly increasing), we propose linear-time algorithms computing a maximal increasing subsequence of an input sequence from an alphabet Σ. Our algorithm for computing a maximal monotone increasing subsequence requires O(1) space and our algorithm for computing a maximal strictly increasing subsequence requires O(|Σ|) space.

Discovering Sequence Association Rules for Protein Structure Prediction (단백질 구조 예측을 위한 서열 연관 규칙 탐사)

  • Kim, Jeong-Ja;Lee, Do-Heon;Baek, Yun-Ju
    • The KIPS Transactions:PartD
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    • v.8D no.5
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    • pp.553-560
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    • 2001
  • Bioinformatics is a discipline to support biological experiment projects by storing, managing data arising from genome research. In can also lead the experimental design for genome function prediction and regulation. Among various approaches of the genome research, the proteomics have been drawing increasing attention since it deals with the final product of genomes, i.e., proteins, directly. This paper proposes a data mining technique to predict the structural characteristics of a given protein group, one of dominant factors of the functions of them. After explains associations among amino acid subsequences in the primary structures of proteins, which can provide important clues for determining secondary or tertiary structures of them, it defines a sequence association rule to represent the inter-subsequences. It also provides support and confidence measures, newly designed to evaluate the usefulness of sequence association rules, After is proposes a method to discover useful sequence association rules from a given protein group, it evaluates the performance of the proposed method with protein sequence data from the SWISS-PROT protein database.

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