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  1. 1
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…All the algorithm for the engine has been developed by using Java script language. …”
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  2. 2
    Phishing attack detection using machine learning method

    Phishing attack detection using machine learning method by Jupin, John Arthur

    Published 2019
    “…The Naïve Bayes algorithm, Decision Tree algorithm and Support Vector Machine algorithm has been used to prevent the spam attack, as well as the phishing attack. …”
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    Undergraduates Project Papers
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  3. 3
    Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi

    Predicting attackers of online shaming using ant colony optimization / Noor Shafiqa Fazlien Mohamad Fauzi by Mohamad Fauzi, Noor Shafiqa Fazlien

    Published 2020
    “…In order to predict the attackers of online shaming, Ant Colony Optimization Algorithm will be used and it will be compared with J48 algorithm. …”
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  4. 4
    A novel algorithm to prevent man in the middle attack in LAN environment

    A novel algorithm to prevent man in the middle attack in LAN environment by Ahmed , Mohiuddin, Hazza, Muataz

    Published 2010
    “…The use of HTTPS gives a sense of protection against attacks such as man in the middle (MITM) attack. …”
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    Proceeding Paper
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  5. 5
    Wormhole attack detection mechanism in mobile ad hoc network using neighborhood information and path tracing algorithm

    Wormhole attack detection mechanism in mobile ad hoc network using neighborhood information and path tracing algorithm by Enshaei, Mehdi

    Published 2015
    “…NIPT algorithm has better improvement on delay which presents the elimination of attacker. …”
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  6. 6
    Cryptanalysis in cryptographic algorithm design

    Cryptanalysis in cryptographic algorithm design by Z'aba, Muhammad Reza, Ahmad, Badrisham, Ibrahim, Subariah, Maarof, Mohd. Aizaini

    Published 2006
    “…In this paper, we review the types of attacks and focus on short-cut attacks. Short-cut attacks make use of an algorithm’s weaknesses to discover the key faster than brute-force. …”
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  7. 7
    Malware Classification and Detection using Variations of Machine Learning Algorithm Models

    Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

    Published 2025
    “…The purpose of the study is to detect, classify malware attacks using a variety of ML Algorithm models such as SVM, KNN and Neural Network and testing detection performance. …”
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  8. 8
    Implement edge pruning to enhance attack graph generation using the naïve approach algorithm

    Implement edge pruning to enhance attack graph generation using the naïve approach algorithm by Al-Araji, Zaid J., Mutlag, Ammar Awad, Syed Ahmad, Sharifah Sakinah

    Published 2024
    “…The attack graph is categorized into three sections: generation, analysis, and use of attack graph. …”
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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
    An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack

    An evaluation on KNN-SVM algorithm for detection and prediction of DDoS attack by Yusof, Ahmad Riza’ain, Udzir, Nur Izura, Selamat, Ali

    Published 2016
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  11. 11
    Predicting the success of suicide terrorist attacks using different machine learning algorithms

    Predicting the success of suicide terrorist attacks using different machine learning algorithms by Hossain, Md Junayed, Abdullah, Sheikh Md, Barkatullah, Mohammad, Miahh, Md Saef Ulla, Sarwar, Talha, Monir, Md Fahad

    Published 2022
    “…For this purpose, various machine learning algorithms, namely Random Forest, K Nearest Neighbor, Decision Tree, LightGBM Boosting, and a feedforward Artificial Neural Network called Multilayer Perceptron (MLP), are used to determine the success of suicide terrorist attacks. …”
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  12. 12
    An Enhanced Mechanism To Detect Drdos Attacks On Dns Using Adaptive Thresholding Technique

    An Enhanced Mechanism To Detect Drdos Attacks On Dns Using Adaptive Thresholding Technique by Al Ogaili, Riyadh Rahef Nuiaa

    Published 2023
    “…Thus, this thesis presents a mechanism for detecting DRDoS attacks on DNS that is strengthened by the use of modified metaheuristic algorithms and adaptive thresholding techniques based on machine learning algorithms (EMDDMAT).…”
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  13. 13
    Cryptanalytic attacks on Rivest, Shamir, and Adleman (RSA) cryptosystem: issues and challenges

    Cryptanalytic attacks on Rivest, Shamir, and Adleman (RSA) cryptosystem: issues and challenges by Abubakar, Adamu, Jabaka, Shehu, Tijani, Bello Idrith, Zeki, Akram M., Chiroma, Haruna, Usman, Mohammed Joda, Raji, Shakirat, Mahmud, Murni

    Published 2014
    “…This paper presents the issues and challenges on some key aspects of cryptanalytic attacks on RSA algorithm. The paper also explores the perceived vulnerabilities of implementing RSA algorithm which can render a cryptanalyst easier means of attack.…”
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  14. 14
    Heart Attack Prediction with Deep Learning

    Heart Attack Prediction with Deep Learning by Syasya Putri binti Mohamad Razauddin

    Published 2023
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  15. 15
    Early detection and mitigation of DDoS attacks in software defined networks

    Early detection and mitigation of DDoS attacks in software defined networks by Al-Saadi, Mustafa Yahya Zakariya

    Published 2018
    “…To detect and mitigate this attack at its early stages, an entropy-based DDoS attack detection and mitigation algorithm was proposed. …”
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  16. 16
    Dynamic determinant matrix-based block cipher algorithm

    Dynamic determinant matrix-based block cipher algorithm by Juremi, Julia

    Published 2018
    “…Analyses on linear, differential and short attack will be performed against the DDBC algorithm to estimate the possible success of all three attacks. …”
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  17. 17
    Attack prediction to enhance attack path discovery using improved attack graph

    Attack prediction to enhance attack path discovery using improved attack graph by Al-Araji, Zaid Jasim, Abdullah, Raihana Syahirah, Syed Ahmad, Sharifah Sakinah

    Published 2022
    “…For the attack graph analysis, the random forest algorithm was used to detect, predict, and dynamically ascertain the attack location in the network. …”
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  18. 18
    Detecting resource consumption attack over MANET using an artificial immune algorithm

    Detecting resource consumption attack over MANET using an artificial immune algorithm by Abdelhaq, Maha, Hassan, Rosilah, Ismail, Mahamod, Israf Ali, Daud Ahmad

    Published 2011
    “…This paper’s objective is to utilize the biological model used in the dendritic cell algorithm (DCA) to introduce a Dendritic Cell Inspired Intrusion Detection Algorithm (DCIIDA). …”
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  19. 19
    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm

    Novel approach for IP-PBX denial of service intrusion detection using support vector machine algorithm by Jama, Abdirisaq M., Khalifa, Othman Omran, Subramaniam, Nantha Kumar

    Published 2021
    “…The time taken by the algorithms to classify the attack is very important. …”
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  20. 20
    An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm

    An efficient attack detection for Intrusion Detection System (IDS) in internet of medical things smart environment with deep learning algorithm by Abdulkareem, Fatimah Saleem, Mohd Sani, Nor Fazlida

    Published 2023
    “…Additionally, the results of the deep learning algorithms will be evaluated using five confusion matrices, namely, accuracy, precision, recall, F1Score, and false-positive rate). …”
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