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  1. 1
    Real-Time Video Processing Using Native Programming on Android Platform

    Real-Time Video Processing Using Native Programming on Android Platform by Saipullah, Khairul Muzzammil

    Published 2012
    “…However for the Android platform that based on the JAVA language, most of the software algorithm is running on JAVA that consumes more time to be compiled. …”
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  2. 2
    A malware analysis and detection system for mobile devices / Ali Feizollah

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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  3. 3
    Machine learning algorithms in context of intrusion detection

    Machine learning algorithms in context of intrusion detection by Mehmood, T., Rais, H.B.Md.

    Published 2016
    “…Although, signature based has high detection rate but it cannot detect novel attacks. …”
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  4. 4
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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  5. 5
    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
    “…Experimental results show the proposed technique increases accuracy classification percentage up to 99.95%; and the minimum number of bins determine good discretization algorithm. Consequently, attack detection rate increases and false positive alarm rate minimizes. …”
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  6. 6
    Artificial immune system based on real valued negative selection algorithms for anomaly detection

    Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

    Published 2015
    “…Experimental results illustrate that RNSA and V-Detector algorithms are suitable for the detection of anomalies, with SVM and KNN producing significant efficiency rates and increase in execution time. …”
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  7. 7
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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  8. 8
    Energy detection for spectrum sensing in OFDM-based cooperative and non-cooperative radio networks

    Energy detection for spectrum sensing in OFDM-based cooperative and non-cooperative radio networks by Salman, Emad Hmood

    Published 2018
    “…Next, we developed a Constant Global False Alarm Rate (CGFAR) with Constant Global Detection Rate (CGDR) algorithm to mitigate the Cooperative SS (CSS) requirements. …”
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  9. 9
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  10. 10
    Experimenting the dendrite cell algorithm for disease outbreak detection model

    Experimenting the dendrite cell algorithm for disease outbreak detection model by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza

    Published 2014
    “…To achieve that, an anthrax disease outbreak is chosen as a case study.Two artificial anthrax datasets known as WSARE7 and WSARE58 are taken as experiment data.The experiment is measured based on five metrics; detection rate, specificity, false alarm rate, accuracy, and time taken to produce result. …”
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  11. 11
    Provider independent cryptographic tools

    Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

    Published 2003
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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
    “…GAs are search algorithms which are based on the principles of natural selection and genetics. …”
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  13. 13
    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level

    Cloud Worm Detection and Response Technique By Integrating The Enhanced Genetic Algorithm An Threat Level by Hasan Mahmoud Sha'ban Kanaker

    Published 2024
    thesis::doctoral thesis
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  14. 14
    Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband

    Cooperative multi agents for intelligent intrusion detection and prevention systems / Shahaboddin Shamshirband by Shamshirband, Shahaboddin

    Published 2014
    “…Later, we investigate the game based-FQL algorithm by combining the game theoretic approach and the fuzzy Q-learning algorithm. …”
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  15. 15
    Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.]

    Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.] by Mohd Fuzi, Mohd Faris, Mohd Shahirudin, Syamir, Abd Halim, Iman Hazwam, Jamaluddin, Muhammad Nabil Fikri

    Published 2023
    “…With the advancement of malware analysis, Machine Learning (ML) is increasingly being used to detect malware. This study's major objective is to compare the best-supervised ML algorithms for malware detection based on detection accuracy. …”
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  16. 16
    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
    “…For CICIDS dataset, SVM algorithm achieved highest detection rate of 76.47% while decision tree and Naïve Bayes has 63.71% & 41.58% of detection rate, respectively. …”
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  17. 17
    Analysis of artificial neural network and viola-jones algorithm based moving object detection

    Analysis of artificial neural network and viola-jones algorithm based moving object detection by Rashidan, M. Ariff, Mohd Mustafah, Yasir, Zainal Abidin, Zulkifli, Zainuddin, N. Afiqah, A. Aziz, Nor Nadirah

    Published 2014
    “…The utilization of cascade architecture to the extracted features, benefits the algorithm. The algorithms have been tested on simulated events, and the more suitable algorithm with high detection rate is expected to be presented in this paper.…”
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  18. 18
    Fetal heart rate monitoring during pregnancy for assessing the well-being of the fetus

    Fetal heart rate monitoring during pregnancy for assessing the well-being of the fetus by Ibrahimy, Muhammad Ibn

    Published 2018
    “…The performance of the algorithm has been evaluated of the heart rates tracing processed from the abdominal signals. …”
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  19. 19
    An evolutionary harmony search algorithm with dominant point detection for recognition-based segmentation of online Arabic text recognition

    An evolutionary harmony search algorithm with dominant point detection for recognition-based segmentation of online Arabic text recognition by Moayad, Yousif Potrus, Ngah, Umi Kalthum, Bestoun S. , Ahmed

    Published 2014
    “…This paper highlights a novel strategy for online Arabic text recognition using a hybrid Genetic Algorithm (GA) and Harmony Search algorithm (HS). The strategy is divided into two phases: text segmentation using dominant point detection, and recognition-based segmentation using GA and HS. …”
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  20. 20
    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi

    Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

    Published 2019
    “…An efficient IDS uses computational methods as techniques of machine learning (ML) to enhance the rates of detection to obtain the lowest false positive rate, although such rates tend to be reduced by the big amount of irrelevant features as an optimization issue. …”
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