The rise of “malware”: Bibliometric analysis of malware study

MF Ab Razak, NB Anuar, R Salleh, A Firdaus - Journal of Network and …, 2016 - Elsevier
Malicious software (malware) is a computer program designed to create harmful and
undesirable effects. It considered as one of the many dangerous threats for Internet users …

A comprehensive survey of network traffic anomalies and DDoS attacks detection schemes using fuzzy techniques

H Lin, C Wu, M Masdari - Computers and Electrical Engineering, 2022 - Elsevier
Anomaly intrusion detection systems are a class of intrusion detection systems that do not
rely on the security attacks' signatures and focus on finding unknown malicious behaviors …

Aesmote: Adversarial reinforcement learning with smote for anomaly detection

X Ma, W Shi - IEEE Transactions on Network Science and …, 2020 - ieeexplore.ieee.org
Intrusion Detection Systems (IDSs) play a vital role in securing today's Data-Centric
Networks. In a dynamic environment such as the Internet of Things (IoT), which is vulnerable …

Adaptive neuro-fuzzy maximal power extraction of wind turbine with continuously variable transmission

D Petković, Ž Ćojbašić, V Nikolić, S Shamshirband… - Energy, 2014 - Elsevier
In recent years the use of renewable energy including wind energy has risen dramatically.
Because of the increasing development of wind power production, improvement of the …

Discovering optimal features using static analysis and a genetic search based method for Android malware detection

A Firdaus, NB Anuar, A Karim, MFA Razak - Frontiers of Information …, 2018 - Springer
Mobile device manufacturers are rapidly producing miscellaneous Android versions
worldwide. Simultaneously, cyber criminals are executing malicious actions, such as …

An anomaly-based intrusion detection system in presence of benign outliers with visualization capabilities

A Karami - Expert Systems with Applications, 2018 - Elsevier
Abnormal network traffic analysis through Intrusion Detection Systems (IDSs) and
visualization techniques has considerably become an important research topic to protect …

A study of machine learning classifiers for anomaly-based mobile botnet detection

A Feizollah, NB Anuar, R Salleh… - Malaysian Journal of …, 2013 - adum.um.edu.my
In recent years, mobile devices are ubiquitous. They are employed for purposes beyond
merely making phone calls. Among the mobile operating systems, Android is the most …

Analysis of intruder detection in big data analytics

KM Sudar, P Nagaraj, P Deepalakshmi… - 2021 International …, 2021 - ieeexplore.ieee.org
Network security and data security is gaining vital importance as the usage of applications
on computer networks evolving now-a-days. Tremendous increase of data usage on real …

[HTML][HTML] Towards a systematic description of the field using bibliometric analysis: malware evolution

SRT Mat, MF Ab Razak, MNM Kahar, JM Arif… - Scientometrics, 2021 - Springer
Malware is a blanket term for Trojan, viruses, spyware, worms, and other files that are
purposely created to harm computers, mobile devices, or computer networks. Malware …

Root exploit detection and features optimization: mobile device and blockchain based medical data management

A Firdaus, NB Anuar, MFA Razak, IAT Hashem… - Journal of medical …, 2018 - Springer
The increasing demand for Android mobile devices and blockchain has motivated malware
creators to develop mobile malware to compromise the blockchain. Although the blockchain …