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

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

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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

Systematic analysis on mobile botnet detection techniques using genetic algorithm by Rahman M.Z.A., Madihah Mohd Saudi

Systematic Analysis on Mobile Botnet Detection Techniques Using Genetic Algorithm by Rahman, MZA, Madihah Mohd Saudi

“…A case study was carried out to reverse engineering the mobile botnet codes. Based on the findings, this mobile botnet has successfully posed itself as a fake anti-virus and has the capability to steal important data such as username and password from the Android-based devices. …”

ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

“…Due to the fast modifications in the technologies used by malicious application (app) developers, there is an urgent need for more advanced techniques for Android botnet detection. In this paper, a new approach for Android botnet classification based on features selection and classification algorithms is proposed. …”
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A comprehensive review of mobile botnet detection using genetic algorithm: A systematic review by Abd Rahman M.Z.B., Saudi M.B.M., Basir N.B.

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

“…This new classification can be used as the input for mobile botnet detection for future work, especially for financial matters.…”

Layered Botnet Detection Framework Based On Signal Processing And Discrete Time Analysis by Melhim, Loai Kayed Hassan Bani

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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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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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ABC: Android botnet classification using feature selection and classification algorithms by Abdullah Z., Anuar N.B., Madihah Mohd Saudi

A behavior based algorithm to detect spam bots by Zamil, Mohammed Fadhil

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IoT-based botnet attacks systematic mapping study of literature by Habiba Hamid, Rafidah Md Noor, Syaril Nizam Omar, Ismail Ahmedy, Shaik Shabana Anjum, Syed Adeel Ali Shah, Sheena Kaur, Fazidah Othman, Emran Mohd Tamil

Intersection Features For Android Botnet Classification by Ismail, Najiahtul Syafiqah, Yusof, Robiah, Saad, Halizah, Abdollah, Mohd Faizal, Yusof, Robiah

“…This paper proposed an enhancement approach for Android botnet classification based on features selection and classification algorithms. …”
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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

“…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.

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

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Android mobile malware detection model based on permission features using machine learning approach by Sharfah Ratibah, Tuan Mat

“…Different techniques have been adopted to detect and prevent the spread of Android malware, including anomaly, signature-based, and hybrid detection techniques. …”
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Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

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An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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