Search Results - (( botnet detection learning algorithm ) OR ( java application optimisation algorithm ))

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    Botnet Detection in IoT Devices Using Random Forest Classifier with Independent Component Analysis by Akash, Nazmus Sakib, Rouf, Shakir, Jahan, Sigma, Chowdhury, Amlan, Uddin, Jia

    Published 2022
    “…This paper represents a model that accounts for the detection of botnets through the use of machine learning algorithms. …”
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    Article
  3. 3

    A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

    Published 2024
    “…The experimental result shows that the Random Forest Algorithm has achieved the highest detection accuracy of 99.4% with the lowest false positive rate of 16.1% as compared to other machine learning algorithms. …”
    Proceedings Paper
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    A Static Approach towards Mobile Botnet Detection by Shahid, Anwar, Jasni, Mohamad Zain, Inayat, Zakira, Ul Haq, Riaz, Ahmad, Karim, Jaber, Aws Naser

    Published 2016
    “…In this study we propose a static approach towards mobile botnet detection. This technique combines MD5, permissions, broadcast receivers as well as background services and uses machine learning algorithm to detect those applications that have capabilities for mobile botnets. …”
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    Conference or Workshop Item
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    A smart framework for mobile botnet detection using static analysis by Anwar, Shahid, Mohamad Fadli, Zolkipli, Mezhuyev, Vitaliy, Inayat, Zakira

    Published 2020
    “…This study proposes a smart framework for mobile botnet detection using static analysis. This technique combines permissions, activities, broadcast receivers, background services, API and uses the machine-learning algorithm to detect mobile botnets applications. …”
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    Article
  8. 8

    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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    Designing a New Model for Trojan Horse Detection Using Sequential Minimal Optimization by Saudi, MM, Abuzaid, AM, Taib, BM, Abdullah, ZH

    Published 2024
    “…Based on the experiment conducted, the Sequential Minimal Optimization (SMO) algorithm has outperformed other machine learning algorithms with 98.2 % of true positive rate and with 1.7 % of false positive rate.…”
    Proceedings Paper
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    Secure IIoT-enabled industry 4.0 by Zeeshan Hussain, Adnan Akhunzada, Javed Iqbal, Iram Bibi, Abdullah Gani

    Published 2021
    “…IIoT-enabled botnets are highly scalable, technologically diverse, and highly resilient to classical and conventional detection mechanisms. …”
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    Article
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    Automated System for Detecting Cyber Bot Attacks in 5G Networks using Machine Learning by Thrupthi, C.P., Chitra, K., Harilakshmi, V.M.

    Published 2024
    “…Machine learning algorithms have been proposed to identify bot networks with a focus on extracting features from high-dimensional datasets. …”
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    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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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
    “…Both samples of datasets then were evaluated using machine learning and deep learning approaches to analyse the best accuracy of malware detection. …”
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    Thesis
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    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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    Thesis