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  1. 1
    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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  2. 2
    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
    “…The proposed attack graph reduced the generation time by 20% and the attack graph complexity. …”
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  3. 3
    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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  4. 4
    Attacks detection in 6G wireless networks using machine learning

    Attacks detection in 6G wireless networks using machine learning by Saeed, Mamoon M., Saeed, Rashid A., Gaid, Abdulguddoos S. A., Mokhtar, Rania A., Khalifa, Othman Omran, Ahmed, Zeinab E.

    Published 2023
    “…The Attacks Detection in 6G (AD6Gs) wireless networks created by this research uses a Machine Learning (ML) algorithm. …”
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  5. 5
    Cloud co-residency denial of service threat detection inspired by artificial immune system

    Cloud co-residency denial of service threat detection inspired by artificial immune system by Ahmad A., Shafiuddin W., Kama M.N., Idris N.B., Madihah Mohd Saudi

    Published 2024
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  6. 6
    Campus hybrid intrusion detection system using SNORT and C4.5 Algorithm

    Campus hybrid intrusion detection system using SNORT and C4.5 Algorithm by Slamet, ., Izzeldin, I. Mohd, Fahmi, Samsuri

    Published 2020
    “…As a result of implementing this system: misused detection module uses the signature of attacks to detection the known attacks; anomaly detection module can detect the unknown attacks; signature generation module extracts the signature of attacks that are detected by Anomaly Detection System module, and maps the signatures into snort rules.…”
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  7. 7
    Cloud Co-Residency Denial of Service Threat Detection Inspired by Artificial Immune System

    Cloud Co-Residency Denial of Service Threat Detection Inspired by Artificial Immune System by Ahmad, A, Zainuddin, WS, Kama, MN, Idris, NB, Saudi, MM

    Published 2024
    “…The experiment was conducted in a controlled environment and conducted using custom generated co-residency denial of service attacks for testing the capability of the proposed model in detecting novel co-residency attacks. …”
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  8. 8
    Social engineering exploitation detection (SEED) in Malaysia's SMEs using machine learning

    Social engineering exploitation detection (SEED) in Malaysia's SMEs using machine learning by Sia, Ken Yen

    Published 2022
    “…Most of the current detection models only provide a guideline framework in detecting such attacks which is not efficient or with low accuracy. …”
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  9. 9
    An enhancement of classification technique based on rough set theory for intrusion detection system application

    An enhancement of classification technique based on rough set theory for intrusion detection system application by Noor Suhana, Sulaiman

    Published 2019
    “…An Intrusion Detection System (IDS) is capable to detect unauthorized intrusions into computer systems and networks by looking for signatures of known attacks or deviations of normal activity. …”
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  10. 10
    Cloud co-residency denial of service threat detection inspired by artificial immune system

    Cloud co-residency denial of service threat detection inspired by artificial immune system by Ahmad, Azuan, Zainudin, Wan Shafiuddin, Kama, Mohd Nazri, Idris, Norbik Bashah, Mohd Saudi, Madihah

    Published 2018
    “…The experiment was conducted in a controlled environment and conducted using custom generated co-residency denial of service attacks for testing the capability of the proposed model in detecting novel co-residency attacks. …”
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  11. 11
    Design and analysis of an early heart attack detection using openCV

    Design and analysis of an early heart attack detection using openCV by Muhammad Rafsanjani, Basri, Fahmi, Samsuri

    Published 2022
    “…Early detection of heart attack symptoms is a crucial part of treatment at the moment. …”
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  12. 12
    Improving intrusion detection using genetic algorithm

    Improving intrusion detection using genetic algorithm by Hashemi, V. Moraveji, Muda, Zaiton, Yassin, Warusia

    Published 2013
    “…A great deal of attention has been recently paid to anomaly detection to accomplish intrusion detection. However, a major problem with this approach is maximizing detection rate and accuracy, as well as minimizing false alarm i.e., inability to correctly discover particular types of attacks. …”
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  13. 13
    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System

    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…As network attackers keep changing their methods of attack execution to evade the deployed intrusion-detection systems (IDS), machine learning (ML) algorithms have been introduced to boost the performance of the IDS. …”
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  14. 14
    An improved method using fuzzy system based on hybrid boahs for phishing attack detection

    An improved method using fuzzy system based on hybrid boahs for phishing attack detection by Noor Syahirah, Nordin

    Published 2022
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  15. 15
    ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs

    ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs by Khan, T., Singh, K., Hasan, M.H., Ahmad, K., Reddy, G.T., Mohan, S., Ahmadian, A.

    Published 2021
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  16. 16
    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 first step in our work was to generate the DNS traffic in normal and attack situations for using as the input of our intrusion detection system (IDS). …”
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  17. 17
    Security alert framework using dynamic tweet-based features for phishing detection on twitter

    Security alert framework using dynamic tweet-based features for phishing detection on twitter by Liew, Seow Wooi

    Published 2019
    “…Many phishing detection methods, ranging from blacklists, heuristics and visual similarity to machine learning are used to detect phishing attacks for spam emails, machine learning approaches achieve the best phishing email detection results. …”
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  18. 18
    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices

    Optimization of blood vessel detection in retina images using multithreading and native code for portable devices by Tran, Duc Ngoc, Hussin, Fawnizu Azmadi, Yusoff, Mohd Zuki

    Published 2013
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  19. 19
    Detection of SQL injection attack using machine learning

    Detection of SQL injection attack using machine learning by Tung, Tean Thong

    Published 2024
    “…The system will undergo real-time monitoring through periodic analysis of website traffic statistics. Upon detection of a SQLI attack, the system will generate and transmit a comprehensive report to promptly warn the network administrator of the occurrence of the attack. …”
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  20. 20
    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets

    ICS cyber attack detection with ensemble machine learning and DPI using cyber-Kit datasets by Mubarak, Sinil, Habaebi, Mohamed Hadi, Islam, Md. Rafiqul, Khan, Sheroz

    Published 2021
    “…The processed metadata is normalized for the easiness of algorithm analysis and modelled with machine learning-based latest deep learning ensemble LSTM algorithms for anomaly detection. …”
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