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A new mobile botnet classification based on permission and API calls by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

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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

“…This paper represents a model that accounts for the detection of botnets through the use of machine learning algorithms. …”
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A New Mobile Botnet Classification based on Permission and API Calls by Yusof, M, Saudi, MM, Ridzuan, F

“…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. …”

Back Propagation Algorithm-Based Intelligent Model for Botnet Detection by Nik Quosthoni, Sunaidi, Ahmed, Abdulghani Ali

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Machine Learning For HTTP Botnet Detection Using Classifier Algorithms by Mohd Dollah, Rudy Fadhlee, Abd Majid, Mohd Faizal, Arif, Fahmi, Mas'ud, Mohd Zaki, Lee, Kher Xin

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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

“…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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A smart framework for mobile botnet detection using static analysis by Anwar, Shahid, Mohamad Fadli, Zolkipli, Mezhuyev, Vitaliy, Inayat, Zakira

“…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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An enhanced android botnet detection approach using feature refinement by Anwar, Shahid

“…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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Mobile botnet classification by using hybrid analysis by Yusof M., Madihah Mohd Saudi, Farida Hazwani Mohd Ridzuan

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

“…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.…”

Designing a new model for Trojan horse detection using sequential minimal optimization by Madihah Mohd Saudi, Abuzaid A.M., Taib B.M., Abdullah Z.H.

Secure IIoT-enabled industry 4.0 by Zeeshan Hussain, Adnan Akhunzada, Javed Iqbal, Iram Bibi, Abdullah Gani

“…IIoT-enabled botnets are highly scalable, technologically diverse, and highly resilient to classical and conventional detection mechanisms. …”
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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.

“…Machine learning algorithms have been proposed to identify bot networks with a focus on extracting features from high-dimensional datasets. …”
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Android mobile malware detection model based on permission features using machine learning approach by Sharfah Ratibah, Tuan Mat

“…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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Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar by Mohamed Azhar, Nur Afiqah

“…Therefore, numerical method in the form of bracketing method is often used to find only the approximate root of the function. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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Determining the preprocessing clustering algorithm in radial basis function neural network by S.L. Ang, H.C. Ong, H.C. Law

“…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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Genetic Algorithms In Optimizing Membership Function For Fuzzy Logic Controller by Ismail, H. Muh Yusuf

“…Thus it is important to select the accurate membership functions but these methods possess one common weakness where conventional FLC use membership function and control rules generated by human operator. …”
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The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin by Shamsudin, Siti Nur Hafiza

“…The global convergence result is established using exact line searches. Numerical result shows that algorithm 2 which is one of the proposed CG methods is more efficiency when compared to other algorithms.…”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm by Dalatu, Paul Inuwa

“…It shows that the IQR-HEOM method is more efficient to rectify the problem caused by using range in HEOM. …”
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