Fuzzy analytical hierarchy process based risk assessment for malware detection in android mobile system

QR Code

Fuzzy analytical hierarchy process based risk assessment for malware detection in android mobile system

Android mobile devices record a large number of users and are accessible via open source. The openness of the Android mobile devices is extremely vulnerable to malware attacks. Even though various antivirus or security devices are installed in the mobile device, users are still exposed to malware at...

Full description

Bibliographic Details
Main Author:	Juliza, Mohamad Arif
Format:	Thesis
Language:	English
Published:	2022
Subjects:	Q Science (General) QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/37674/ http://umpir.ump.edu.my/id/eprint/37674/1/ir.Fuzzy%20analytical%20hierarchy%20process%20based%20risk%20assessment%20for%20malware%20detection%20in%20android%20mobile%20system.pdf

Similar Items

Android mobile malware detection using Fuzzy AHP
by: Juliza, Mohamad Arif, et al.
Published: (2021)

Android mobile malware detection system using fuzzy AHP
by: Juliza, Mohamad Arif, et al.
Published: (2021)

A Bayesian probability model for Android malware detection
by: Sharfah Ratibah, Tuan Mat, et al.
Published: (2021)

Applying Bayesian probability for Android malware detection using permission features
by: Sharfah Ratibah, Tuan Mat, et al.
Published: (2021)

Machine Learning Malware Detection For Android
by: Amir Muhammad Hafiz, Othman
Published: (2022)

Android mobile malware detection model based on permission features using machine learning approach
by: Sharfah Ratibah, Tuan Mat
Published: (2022)

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

Malware Detection In Android Using Machine Learning
by: Muhammad Hazriq Akmal, Zairol
Published: (2023)

Techniques for analysing android malware
by: Adebayo, Olawale Surajudeen, et al.
Published: (2014)

Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA)
by: Nur Khairani, Kamarudin, et al.
Published: (2023)

A behaviour-based analytical malware detection framework for android smartphones
by: Damshenas, Mohsen
Published: (2014)

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

Permission extraction framework for android malware detection
by: Ghasempour, Ali
Published: (2019)

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

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

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

The trend of mobile malwares and effective detection techniques
by: Abdul Aziz, Normaziah, et al.
Published: (2015)

Discovering optimal features using static analysis and a genetic search based method for Android malware detection
by: Ahmad Firdaus, Zainal Abidin, et al.
Published: (2018)

A rooting detection system and risk assessment for android mobile devices / Wael Farouk Mohamed Elsersy
by: Wael Farouk , Mohamed Elsersy
Published: (2022)

Evaluating Neural Network Intrusion Detection Approaches Using Analytic Hierarchy Process
by: Ahmad, iftikhar, et al.
Published: (2010)

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

Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
by: Adebayo, Olawale Surajudeen, et al.
Published: (2014)

Dawn Of The Mobile Malware: Reviewing Mobile Worms .
by: Sarwar, Usman, et al.
Published: (2007)

A malware risk analysis and detection system for mobile devices using permission-based features / Mohd Faizal Ab Razak
by: Mohd Faizal , Ab Razak
Published: (2018)

Bio-inspired for Features Optimization and Malware Detection
by: Mohd Faizal, Ab Razak, et al.
Published: (2018)

Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
by: Adebayo, Olawale Surajudeen, et al.
Published: (2015)

Hybrid fuzzy analytical hierarchy process with fuzzy inference system on ranking stem approach towards blended learning in mathematics
by: Durrani Aimi, Abdul Malik
Published: (2022)

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

Malware detection through machine learning techniques
by: Amer, Ahmed, et al.
Published: (2019)

Ensemble based categorization and adaptive model for malware detection
by: Ahmad Zabidi, Muhammad Najmi, et al.
Published: (2011)

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

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

Towards a systematic description of the field using bibliometric analysis: malware evolution
by: Sharfah Ratibah, Tuan Mat, et al.
Published: (2021)

Mobile malware anomaly-based detection systems using static analysis features / Ahmad Firdaus Zainal Abidin
by: Ahmad Firdaus, Zainal Abidin
Published: (2017)

Halal compliance decisions by food suppliers based on analytic hierarchy process
by: Iberahim, Hadijah, et al.
Published: (2016)

Convolutional Long Short-Term Memory for fileless malware detection
by: Kareegalan, Kunaprasan
Published: (2024)

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)

Features, Analysis Techniques, and Detection Methods of Cryptojacking Malware: A Survey
by: Kadhum, Laith M., et al.
Published: (2024)

Android malware detection using permission based static analysis
by: Mohd Ariffin, Noor Afiza, et al.
Published: (2024)