Search Results - (( java implication based algorithm ) OR ( data detection a algorithm ))*

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  1. 1

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
    “…The proposed DetectCombined is an innovated technique that execute a protection code based on a sequence of three stages: filtration-validation-history, this technique produces a robust protection code that distinguish between safe SQL commands and malicious ones, and reinforce the memory of detection procedure by saving previous SQL attacks in special tables in the remote database, regardless of the types of users whether a general user of admin. …”
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    Article
  2. 2

    Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer by Iqbal Basheer, Muhammmad Yunus

    Published 2023
    “…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. …”
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    Thesis
  3. 3

    Missing tags detection algorithm for radio frequency identification (RFID) data stream by Zainudin, Nur 'Aifaa

    Published 2019
    “…Thus in this research, an AC complement algorithm with hashing algorithm and Detect False Negative Read algorithm (DFR) is used to developed the Missing Tags Detection Algorithm (MTDA). …”
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    Thesis
  4. 4

    Adaptive grid-meshed-buffer clustering algorithm for outlier detection in evolving data stream by Abdulateef, Alaa Fareed

    Published 2023
    “…Existing clustering algorithms for outlier detection encounter significant challenges due to insufficient data pre-processing methods and the absence of a suitable data summarization framework for effective data stream clustering. …”
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    Thesis
  5. 5

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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    Thesis
  6. 6

    Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

    Published 2005
    “…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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    Conference or Workshop Item
  7. 7

    A novel steganography algorithm using edge detection and MPC algorithm by Aref Rezaei, Leili Farzinvash, Ali Farzamnia

    Published 2019
    “…In this paper, we propose an efficient steganography algorithm which applies edge detection and MPC algorithm for data concealment in digital images. …”
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    Conference or Workshop Item
  8. 8

    The multiple outliers detection for circular univariate data using different agglomerative clustering algorithms by Nur Syahirah, Zulkipli, Siti Zanariah, Satari, Wan Nur Syahidah, Wan Yusoff

    Published 2024
    “…This study proposes the procedure of detecting multiple outliers, particularly for univariate circular data based on agglomerative clustering algorithms. …”
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  9. 9

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…This shows that the Negative Selection Algorithms are equipped with the capabilities of detecting changes in data, thus appropriate for anomaly detection. …”
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    Thesis
  10. 10

    A novel deadlock detection algorithm for neighbour replication on grid environment by Noriyani, Mohd Zin

    Published 2012
    “…Therefore, an action must be taken to detect and solve this problem. A new framework and algorithm called Neighbour Replication on Grid Deadlock Detection (NRGDD) has been developed to handle deadlock cycles that exist during the transaction in Neighbour Replication on Grid (NRG) environment. …”
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    Thesis
  11. 11

    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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    Monograph
  12. 12

    A hybrid digital watermarking algorithm by Sabinus D'Costa

    Published 2023
    “…A watermarking algorithm consists of the watermark structure, an embedding algorithm and an extraction, or detection, algorithm.…”
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    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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    Thesis
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    Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

    Published 2019
    “…Thus, this study proposes the development of algorithms to detect and classify jamming attacks using a set of parameters on the physical layer and MAC in MANET. …”
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    Thesis
  18. 18

    Using streaming data algorithm for intrusion detection on the vehicular controller area network by Sharmin, Shaila, Mansor, Hafizah, Abdul Kadir, Andi Fitriah, Abdul Aziz, Normaziah

    Published 2022
    “…In this paper, the adapted streaming data Isolation Forest (iForestASD) algorithm has been applied to CAN intrusion detection. …”
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    Proceeding Paper
  19. 19

    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

    Published 2022
    “…Recently, researchers suggested a deep belief network (DBN) algorithm to construct and build a network intrusion detection system (NIDS) for detecting attacks that have not been seen before. …”
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    Thesis
  20. 20

    Unsupervised Anomaly Detection with Unlabeled Data Using Clustering by Chimphlee, Witcha, Abdullah, Abdul Hanan, Md. Sap, Mohd. Noor

    Published 2005
    “…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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    Conference or Workshop Item