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  1. 1
    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection

    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection by Ooi, Hui Ni, Ab Rahman, Nurul Hidayah

    Published 2021
    “…This means that Multilayer Perceptron algorithm can detect APT attack more accurately. …”
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  2. 2
    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection

    A comparative study between deep learning algorithm and bayesian network on Advanced Persistent Threat (APT) attack detection by Ooi, Hui Ni, Ab Rahman, Nurul Hidayah

    Published 2021
    “…This means that Multilayer Perceptron algorithm can detect APT attack more accurately. …”
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  3. 3
    A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works

    A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

    Published 2023
    “…Barium compounds; Cybersecurity; Data mining; Decision trees; Evolutionary algorithms; K-means clustering; Learning algorithms; Malware; Network security; Sodium compounds; Support vector machines; 'current; Comparatives studies; Cyber security; K-means; Machine learning algorithms; Malware attacks; Malware detection; Metaheuristic; Recent researches; Systematic literature review; Nearest neighbor search…”
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  4. 4
    Anomaly-based intrusion detection through K-means clustering and naives Bayes classification

    Anomaly-based intrusion detection through K-means clustering and naives Bayes classification by Mohamed Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md. Nasir

    Published 2013
    “…Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
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  5. 5
    Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification

    Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification by Yassin, Warusia, Udzir, Nur Izura, Muda, Zaiton, Sulaiman, Md Nasir

    Published 2013
    “…Intrusion detection systems (IDSs) effectively balance extra security appliance by identifying intrusive activities on a computer system, and their enhancement is emerging at an unexpected rate.Anomaly-based intrusion detection methods, which employ machine learning algorithms, are able to identify unforeseen attacks. …”
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  6. 6
    An improved hybrid learning approach for better anomaly detection

    An improved hybrid learning approach for better anomaly detection by Mohamed Yassin, Warusia

    Published 2011
    “…Nonetheless, current anomaly detection techniques are unable to detect all types of attacks accurately and correctly. …”
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  7. 7
    KM-NEU: an efficient hybrid approach for intrusion detection system

    KM-NEU: an efficient hybrid approach for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia, Udzir, Nur Izura

    Published 2014
    “…The anomaly-based Intrusion Detection Systems (IDS) are able to detect unknown attacks. …”
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  8. 8
    Hybrid intelligent approach for network intrusion detection

    Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

    Published 2015
    “…Hence, there must be substantial improvement in network intrusion detection techniques and systems. Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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  9. 9
    Attack graph construction for enhancing intrusion prediction based on vulnerabilities metrics

    Attack graph construction for enhancing intrusion prediction based on vulnerabilities metrics by Al-Araji, Zaid Jasim Mohammed

    Published 2023
    “…This study employs use Random Forest algorithm to identify and forecast attacks to dynamically locate the attack location in the network for attack graph analysis. …”
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  10. 10
    A hybrid framework based on neural network MLP and means clustering for intrusion detection system

    A hybrid framework based on neural network MLP and means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

    Published 2013
    “…Concerning the robustness of K-means method and MLP algorithms benefits, this research is the part of an effort to develop a hybrid information detection system (IDS) which is able to detect high percentage of novel attacks while keep the false alarm at low rate.This paper provides the conceptual view and a general framework of the proposed system.…”
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  11. 11
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…The simulation is implemented with iFogSim and java programming language. …”
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  12. 12
    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling

    Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

    Published 2011
    “…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. …”
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  13. 13
    A new sinkhole attack detection algorithm for RPL in wireless sensor networks (WSN)

    A new sinkhole attack detection algorithm for RPL in wireless sensor networks (WSN) by Ali, Mohammed Qasim

    Published 2019
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  14. 14
    A hybrid framework based on neural network MLP and K-means clustering for intrusion detection system

    A hybrid framework based on neural network MLP and K-means clustering for intrusion detection system by Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia

    Published 2013
    “…Concerning the robustness of K-means method and MLP algorithms benefits, this research is the part of an effort to develop a hybrid information detection system (IDS) which is able to detect high percentage of novel attacks while keep the false alarm at low rate. …”
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  15. 15
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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  16. 16
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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  17. 17
    Anomaly-based intrusion detection using fuzzy rough clustering

    Anomaly-based intrusion detection using fuzzy rough clustering by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, M. N. M, Srinoy, Surat, Chimphlee, Siriporn

    Published 2006
    “…It is an important issue for the security of network to detect new intrusion attack and also to increase the detection rates and reduce false positive rates in Intrusion Detection System (IDS). …”
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  18. 18
    Enhancement of most significant bit (MSB) algorithm using discrete cosine transform (DCT) in non-blind watermarking / Halimah Tun Abdullah

    Enhancement of most significant bit (MSB) algorithm using discrete cosine transform (DCT) in non-blind watermarking / Halimah Tun Abdullah by Abdullah, Halimah Tun

    Published 2014
    “…According to how watermark detected and extracted, this project use non-blind watermarking mean need an original image during extraction process. …”
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  19. 19
    Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model

    Dynamic feature selection model for adaptive cross site scripting attack detection using developed multi-agent deep Q learning model by Kareem Thajeel, Isam, Samsudin, Khairulmizam, Hashim, Shaiful Jahari, Hashim, Fazirulhisyam

    Published 2023
    “…This approach can be deployed as an autonomous detection system without the need for any offline retraining process of the model to detect the evolved XSS attack.…”
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  20. 20
    A hybrid intrusion detection system based on different machine learning algorithms

    A hybrid intrusion detection system based on different machine learning algorithms by Atefi, Kayvan, Yahya, Saadiah, Dak, Ahmad Yusri, Atefi, Arash

    Published 2013
    “…There are numerous study in intrusion detection system (IDS) especially with Genetic algorithms (GA) and Support Vector Machine (SVM) but most of them did not get the potential of hybrid SVM using GA. …”
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