Efficient feature selection analysis for accuracy malware classification

QR Code

Efficient feature selection analysis for accuracy malware classification

Android is designed for mobile devices and its open-source software. The growth and popularity of android platform are high compared to another platform. Due to its glory, the number of malware has been increasing exponentially. Android system used a permission mechanism to allow users and developer...

Full description

Bibliographic Details
Main Authors:	Rahiwan Nazar, Romli, Mohamad Fadli, Zolkipli, Mohd Zamri, Osman
Format:	Conference or Workshop Item
Language:	English
Published:	IOP Publishing 2021
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/31984/ http://umpir.ump.edu.my/id/eprint/31984/1/Efficient%20feature%20selection%20analysis%20for%20accuracy%20malware%20classification.pdf

Similar Items

Maldroid- attribute selection analysis for malware classification
by: Rahiwan Nazar, Romli, et al.
Published: (2019)

Android: S-Based Technique in Mobile Malware Detection
by: Rahiwan Nazar, Romli, et al.
Published: (2018)

Malware visualizer: A web apps malware family classification with machine learning
by: Mohd Zamri, Osman, et al.
Published: (2021)

Understanding the root of attack in android malware
by: Rahiwan Nazar, Romli, et al.
Published: (2018)

A framework for malware identification based on behavior
by: Mohamad Fadli, Zolkipli
Published: (2012)

Malware detection using static analysis in android: A review of FeCO (features, classification, and obfuscation)
by: Rosmalissa, Jusoh, et al.
Published: (2021)

Malware Analysis with Multiple Features
by: Ahmad Zabidi, Muhammad Najmi, et al.
Published: (2012)

Understanding the root of attack in android malware
by: Romli, Rahiwan Nazar, et al.
Published: (2018)

The Rise of “malware”: Bibliometric Analysis of Malware Study
by: Mohd Faizal, Ab Razak, et al.
Published: (2016)

Malware classification based on target location
by: Nasuha, Noor Baha
Published: (2014)

Deep learning based hybrid analysis of malware detection and classification: A recent review
by: Hussain, Syed Shuja, et al.
Published: (2023)

Bio-Inspired Computational Paradigm for Feature Investigation and Malware Detection: Interactive Analytics
by: Ahmad, Firdaus, et al.
Published: (2017)

Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF)
by: Mazlan, Nurul Hidayah
Published: (2019)

A review of feature selection on text classification
by: Nur Syafiqah, Mohd Nafis, et al.
Published: (2018)

Android malware detection with ensemble of androidmanifest features
by: Mohammad Salehi, .
Published: (2019)

A review : Static analysis of android malware and detection technique
by: Juliza, Mohamad Arif, et al.
Published: (2021)

A malware analysis and detection system for mobile devices / Ali Feizollah
by: Ali, Feizollah
Published: (2017)

A static analysis approach for android permission-based malware detection systems
by: Juliza, Mohamad Arif, et al.
Published: (2021)

Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
by: Rachmad, Iqbal, et al.
Published: (2024)

Study of graphical authentication system based on persuasive rotation, resizing and cued click point (GUAS)
by: Zolkipli, Mohamad Fadli
Published: (2014)

Battery Efficiency of Mobile Devices through Computational Offloading: A Review
by: Ali, Mushtaq, et al.
Published: (2015)

Challenges in high accuracy of malware detection
by: Ahmad Zabidi, Muhammad Najmi, et al.
Published: (2012)

Review of hybrid analysis technique for malware detection
by: Yus Kamalrul, Mohamed Yunus, et al.
Published: (2020)

Evaluation of feature selection algorithm for android malware detection
by: Mazlan, Nurul Hidayah, et al.
Published: (2018)

Malware detection system using cloud sandbox, machine learning
by: Mail, Mohd Azuwan Efendy, et al.
Published: (2022)

Malware detection using n-gram with TF-IDF weighting
by: Natasha, Zainal
Published: (2018)

Feature selection based on particle swarm optimization algorithm for sentiment analysis classification
by: Nurcahyawati, Vivine, et al.
Published: (2021)

Determining the best weightage feature in parameterization process of GCCD model for clone detection in C-based applications
by: Nurul Syafiqah, Zaidi, et al.
Published: (2023)

Comparison of accuracy performance based on normalization techniques for the features fusion of face and online signature
by: Suryanti, Awang, et al.
Published: (2017)

Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain
by: Ong, Pauline, et al.
Published: (2019)

Detection of colon cancer based on microarray dataset using machine learning as a feature selection and classification techniques
by: A. S. M, Shafi, et al.
Published: (2020)

Review of firewall optimization techniques
by: Shakirah, Saidin, et al.
Published: (2018)

Examining the classification accuracy of TSVMs with feature selection in comparison with the GLAD algorithm
by: Helmi, Hala, et al.
Published: (2011)

A Machine Learning Classification Approach To Detect Tls-Based Malware Using Entropy-Based Flow Set Features
by: Keshkeh, Kinan
Published: (2022)

Performance evaluation of hybrid feature selection technique for sentiment classification based on food reviews
by: Suryanti, Awang, et al.
Published: (2021)

Automated feature selection using boruta algorithm to detect mobile malware
by: Che Akmal, Che Yahaya, et al.
Published: (2020)

Feature level fusion of face and signature using a modified feature selection technique
by: Suryanti, Awang, et al.
Published: (2013)

Intrusion-Detection System Based on Fast Learning Network in Cloud Computing
by: Mohammed Hasan, Ali, et al.
Published: (2018)

Feature selection method based on sparse representation classification for face recognition
by: Boon, Yinn Xi *, et al.
Published: (2014)

Automated web pages classification with integration of principal component analysis (PCA) and independent component analysis (ICA) as feature reduction
by: Sam, Lee Zhi, et al.
Published: (2006)