M
Mohd Faizal Ab Razak
Researcher at Universiti Malaysia Pahang
Publications - 36
Citations - 589
Mohd Faizal Ab Razak is an academic researcher from Universiti Malaysia Pahang. The author has contributed to research in topics: Malware & Computer science. The author has an hindex of 9, co-authored 26 publications receiving 324 citations. Previous affiliations of Mohd Faizal Ab Razak include Information Technology University & University of Malaya.
Papers
More filters
Journal ArticleDOI
The rise of “blockchain”: bibliometric analysis of blockchain study
Ahmad Firdaus,Mohd Faizal Ab Razak,Ali Feizollah,Ibrahim Abaker Targio Hashem,Mohamad Hazim,Nor Badrul Anuar +5 more
TL;DR: Keyword analysis revealed that researchers are adopting blockchain to solve problems in multiple categories of the data research area (data privacy, digital storage, the security of data, big data, and distributed database) and highlighted the utilization and consensus of the algorithm in blockchain research.
Journal ArticleDOI
The rise of malware
TL;DR: The number of papers published by Asian countries such as China, Korea, India, Singapore and Malaysia in relation to the Middle East and North America is discussed and there are several significant impacts of research activities in Asia, in comparison to other continents.
Journal ArticleDOI
Discovering optimal features using static analysis and a genetic search based method for Android malware detection
Ahmad Firdaus,Ahmad Firdaus,Nor Badrul Anuar,Ahmad Karim,Mohd Faizal Ab Razak,Mohd Faizal Ab Razak +5 more
TL;DR: Using genetic search (GS), which is a search based on a genetic algorithm (GA), to select the features among 106 strings, machine learning classifiers were used to evaluate the best features determined by GS, namely, Naïve Bayes (NB), functional trees (FT), J48, random forest (RF), and multilayer perceptron (MLP).
Journal ArticleDOI
Root Exploit Detection and Features Optimization: Mobile Device and Blockchain Based Medical Data Management
Ahmad Firdaus,Nor Badrul Anuar,Mohd Faizal Ab Razak,Mohd Faizal Ab Razak,Ibrahim Abaker Targio Hashem,Syafiq Bachok,Syafiq Bachok,Arun Kumar Sangaiah +7 more
TL;DR: This study proposes to use the bio-inspired method of practical swarm optimization (PSO) which automatically select the exclusive features that contain the novel android debug bridge (ADB) to enhance the machine learning prediction that detects unknown root exploit.
Journal ArticleDOI
Bio-inspired for Features Optimization and Malware Detection
Mohd Faizal Ab Razak,Mohd Faizal Ab Razak,Nor Badrul Anuar,Fazidah Othman,Ahmad Firdaus,Ahmad Firdaus,Firdaus Afifi,Rosli Salleh +7 more
TL;DR: A static analysis technique with machine learning classifier is developed from the permission features noted in the Android mobile device for detecting the malware applications and shows that the use of Android permissions is a potential feature for malware detection.