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    Remote to Local Attack Detection Using Supervised Neural Network by Iftikhar, Ahmad, Azween, Abdullah, Abdullah , S. Alghamdi

    Published 2010
    “…This technique uses sampled dataset from Kddcup99 that is standard for benchmarking of attack detection tools. …”
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    Conference or Workshop Item
  3. 3

    Bio-inspired for Features Optimization and Malware Detection by Mohd Faizal, Ab Razak, Nor Badrul, Anuar, Fazidah, Othman, Ahmad, Firdaus, Firdaus, Afifi, Rosli, Salleh

    Published 2018
    “…The features were optimized from 378 to 11 by using bio-inspired algorithm: particle swarm optimization (PSO). The evaluation utilizes 5000 Drebin malware samples and 3500 benign samples. …”
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    Article
  4. 4

    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
  5. 5

    Bio-inspired for Features Optimization and Malware Detection by Razak, Mohd Faizal Ab, Anuar, Nor Badrul, Othman, Fazidah, Firdaus, Ahmad, Afifi, Firdaus, Salleh, Rosli

    Published 2018
    “…The features were optimized from 378 to 11 by using bio-inspired algorithm: particle swarm optimization (PSO). The evaluation utilizes 5000 Drebin malware samples and 3500 benign samples. …”
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    Article
  6. 6

    Intrusion detection on the in-vehicle network using machine learning by Sharmin, Shaila, Mansor, Hafizah

    Published 2021
    “…This paper presents an intrusion detection method based on the Isolation Forest (iForest) algorithm that detects message insertion attacks using message timing information. …”
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    Proceeding Paper
  7. 7

    Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

    Published 2010
    “…Finally, the algorithm found, which would solve the image segmentation problem.…”
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    Thesis
  8. 8

    Applying Neural Network to U2R Attacks by Iftikhar , Ahmad, Azween, Abdullah, Abdullah , S. Alghamdi

    Published 2010
    “…The system uses sampled data from Kddcup99 dataset, an attack database that is a standard for evaluating the security detection mechanisms. …”
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    Conference or Workshop Item
  9. 9

    Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA) by Nur Khairani, Kamarudin, Ahmad Firdaus, Zainal Abidin, Azlee, Zabidi, Ferda, Ernawan, Syifak, Izhar Hisham, Mohd Faizal, Ab Razak

    Published 2023
    “…Many security practitioners have adopted different approaches to detect malware. However, its attacks continuously evolve and spread, and the number of attacks is still increasing. …”
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    Article
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    Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2016
    “…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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    Book
  12. 12

    An intelligent DDoS attack detection tree-based model using Gini index feature selection method by Bouke, Mohamed Aly, Abdullah, Azizol, ALshatebi, Sameer Hamoud, Abdullah, Mohd Taufik, Atigh, Hayate El

    Published 2023
    “…This paper proposes a novel intelligent DDoS attack detection model based on a Decision Tee (DT) algorithm and an enhanced Gini index feature selection method. …”
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    Article
  13. 13

    A clustering-based method for outlier detection under concept drift by Tahir, Mahjabeen, Abdullah, Azizol, Udzir, Nur Izura, Kasmiran, Khairul Azhar

    Published 2024
    “…The algorithm achieves notable results, with a detection rate of 99.12% on UNSWNB-15 and a 7.9% false positive rate on NSL-KDD, marking significant progress. …”
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    Article
  14. 14

    An enhanced android botnet detection approach using feature refinement by Anwar, Shahid

    Published 2019
    “…In order to detect botnet attacks which causes immense chaos and problems to smartphones, first the Android botnet need to be analysed. …”
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    Thesis
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    Q-Learning-based detection of IPv6 intrusions: a behavioral and performance study by Daru, April Firman, Hirzan, Alauddin Maulana, Mahmod Attar Bashi, Zainab Senan, Fanani, Fajriannoor

    Published 2025
    “…This study launched different ICMPv6 attacks individually and gathered five million samples for each intrusion attack. …”
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    Proceeding Paper
  17. 17

    Precise ICMP Traceback Based On Normal Flow Filtration in Denial of Services Attack by Izaddoost, Alireza

    Published 2008
    “…Intention-driven model, a sampling traceback technique, provides information about the attack flow and able to reconstruct the attack path to the source of attack by the aid of Intrusion Detection system (IDS). …”
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    Thesis
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    Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

    Published 2022
    “…There is yet a non-destructive and in-situ technique explored to detect ergosterol. Capability of NIR to detect few biomarkers such as mycotoxin and zearalenone (ZEN) has been proven to pave the way an effort to explore NIR’s sensitivity towards detecting ergosterol, as discussed in this paper. …”
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    Article
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    Android mobile malware detection model based on permission features using machine learning approach by Sharfah Ratibah, Tuan Mat

    Published 2022
    “…Nevertheless, current technologies indicate that Android malware attackers have find novel ways to avoid detection. …”
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    Thesis
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    A Bayesian probability model for Android malware detection by Sharfah Ratibah, Tuan Mat, Mohd Faizal, Ab Razak, Mohd Nizam, Mohmad Kahar, Juliza, Mohamad Arif

    Published 2021
    “…Different approaches have been adopted to overcome the malware attacks yet this spread is still increasing. To combat this issue, this study proposes an Android malware detection system based on permission features using Bayesian classification. …”
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    Article