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  1. 1
    Direct approach for mining association rules from structured XML data

    Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

    Published 2012
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  2. 2
    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection

    Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2008
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  3. 3
    Study and Implementation of Data Mining in Urban Gardening

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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  4. 4
    SQL Injection Detection using Machine Learning: A Review

    SQL Injection Detection using Machine Learning: A Review by Mohammed A M Oudah, Mohd Fadzli Marhusin

    Published 2024
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  5. 5
    Detection of Denial of Service Attacks against Domain Name System Using Neural Networks

    Detection of Denial of Service Attacks against Domain Name System Using Neural Networks by Rastegari, Samaneh

    Published 2009
    “…The results indicated that the three layered back propagation neural network with a 3-7-3 structure provides a detection rate of 99.55% for direct DoS attacks and 97.82% for amplification DoS attacks. …”
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  6. 6
    An efficient detection model of selective forwarding attacks in wireless mesh networks

    An efficient detection model of selective forwarding attacks in wireless mesh networks by Khanam, Shapla, Saleem, Habibullah Yusuf, Pathan, Al-Sakib Khan

    Published 2012
    “…In our approach, we also propose a multi-hop acknowledgement based algorithm to analyze and detect the malicious behavior to defend against selective forwarding attacks in WMNs. …”
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  7. 7
    Mining Sequential Patterns Using I-PrefixSpan

    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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  8. 8
    A web-based implementation of k-means algorithms

    A web-based implementation of k-means algorithms by Lee, Quan

    Published 2022
    “…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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  9. 9
    Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks

    Machine Learning Based Two Phase Detection and Mitigation Authentication Scheme for Denial-of-Service Attacks in Software Defined Networks by Najmun, Najmun

    Published 2024
    “…In this research, Two-Phase Authentication of Attack Detection (TPAAD) scheme is proposed and investigated for detection and mitigation of DoS attacks in SDN to increase the performance of the above-mentioned issues. …”
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  10. 10
    Mining Sequential Patterns using I-PrefixSpan

    Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

    Published 2008
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    Citation Index Journal
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  11. 11
    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Detecting cyber-security attacks is still a challenging task. …”
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  12. 12
    Security testing of web applications for detecting and removing second-order SQL injection vulnerabilities

    Security testing of web applications for detecting and removing second-order SQL injection vulnerabilities by Draib, Najla'a Ateeq Mohammed

    Published 2022
    “…This technique also applies the removing algorithm, which uses escaping method to remove the detected vulnerabilities. …”
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  13. 13
    RFID-enabled supply chain detection using clustering algorithms

    RFID-enabled supply chain detection using clustering algorithms by Azahar, T.F., Mahinderjit-Singh, M., Hassan, R.

    Published 2015
    “…We propose to use clustering algorithms in order to detect counterfeit in supply chain management. …”
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  14. 14
    A stylometry approach for blind linguistic steganalysis model against translation-based steganography

    A stylometry approach for blind linguistic steganalysis model against translation-based steganography by Mohd Lokman, Syiham

    Published 2023
    “…While targeted steganalysis is designed to attack a specific embedding algorithm, blind steganalysis use features extracted or selection from the medium to detect any anomalies that indicate a possibility that a secret data has been embedded within the medium. …”
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  15. 15
    Energy-efficient intrusion detection in wireless sensor network

    Energy-efficient intrusion detection in wireless sensor network by Salehian, Solmaz, Masoumiyan, Farzaneh, Udzir, Nur Izura

    Published 2012
    “…There are several algorithms for building Intrusion Detection Systems (IDS) based on different WSN routing protocol classifications with respect to energy-efficient manner. …”
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  16. 16
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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  17. 17
    A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework

    A detailed description on unsupervised heterogeneous anomaly based intrusion detection framework by Udzir, Nur Izura, Hajamydeen, Asif Iqbal

    Published 2019
    “…Ultimately, the framework is able to detect a broad range of intrusions exist in the logs without using either the attack knowledge or the traffic behavioural models. …”
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  18. 18
    An enhance embedding method using edge and textures detection for image steganography

    An enhance embedding method using edge and textures detection for image steganography by Al-Maliki, Alaa Jabbar Qasim

    Published 2024
    “…The findings reveal that the proposed method significantly enhances the robustness and security of image steganography, achieving an average Peak Signal-to-Noise Ratio of 18.839 dB and a Structural Similarity Index of 0.647. By embedding in noisy zones using edge and texture detection which complicates feature extraction, making hidden information more secure and statistically less detectable than basic LSB matching techniques. …”
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  19. 19
    Malware detection using Gini, Simpson diversity, and Shannon-Wiener indexes

    Malware detection using Gini, Simpson diversity, and Shannon-Wiener indexes by Yeong Tyng, Ling, Kang Leng, Chiew, Piau, Phang, Xiaowei, Zhang

    Published 2025
    “…The increasing number of malware attacks poses a significant challenge to cyber security. …”
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  20. 20
    Characterizing Current Features of Malicious Threats on Websites

    Characterizing Current Features of Malicious Threats on Websites by Wan Nurulsafawati, Wan Manan, Ahmed, Abdulghani Ali, M. N. M., Kahar

    Published 2019
    “…They compromised computer system, targeting especially to government sector, ecommerce and banking networks rigorously and made it difficult to detect the perpetrators. Attackers used a powerful technique, by embedding a malicious code in a normal webpage that resulted harder detection. …”
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