Security analysis of IoT devices by using mobile computing: a systematic literature review

B Liao, Y Ali, S Nazir, L He, HU Khan - IEEE Access, 2020 - ieeexplore.ieee.org
Internet of Things (IoT) devices are operating in various domains like healthcare
environment, smart cities, smart homes, transportation, and smart grid system. These …

Security in Internet of Things: A review

NA Khan, A Awang, SAA Karim - IEEE access, 2022 - ieeexplore.ieee.org
Internet of Things (IoT) is the paramount virtual network that enables remote users to access
connected multimedia devices. It has dragged the attention of the community because it …

An efficient approach for phishing detection using machine learning

E Gandotra, D Gupta - Multimedia security: algorithm development …, 2021 - Springer
The increasing number of phishing attacks is one of the major concerns of security
researchers today. The traditional tools for identifying phishing websites use signature …

[LIBRO][B] Network intrusion detection using deep learning: a feature learning approach

K Kim, ME Aminanto, HC Tanuwidjaja - 2018 - books.google.com
This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-
art deep learning methods. It also provides a systematic overview of classical machine …

ZeVigilante: Detecting Zero‐Day Malware Using Machine Learning and Sandboxing Analysis Techniques

F Alhaidari, NA Shaib, M Alsafi… - Computational …, 2022 - Wiley Online Library
For the enormous growth and the hysterical impact of undocumented malicious software,
otherwise known as Zero-Day malware, specialized practices were joined to implement …

PROUD-MAL: static analysis-based progressive framework for deep unsupervised malware classification of windows portable executable

SKJ Rizvi, W Aslam, M Shahzad, S Saleem… - Complex & Intelligent …, 2022 - Springer
Enterprises are striving to remain protected against malware-based cyber-attacks on their
infrastructure, facilities, networks and systems. Static analysis is an effective approach to …

Malware detection using machine learning algorithms for windows platform

A Hussain, M Asif, MB Ahmad, T Mahmood… - … and Applications: ICITA …, 2022 - Springer
Windows is a popular Graphical User Interface-based Operating System that provides
services like storage, run third-party software, play videos, network connection, etc. The …

Convolution Neural Network‐Based Higher Accurate Intrusion Identification System for the Network Security and Communication

Z Gu, S Nazir, C Hong, S Khan - Security and Communication …, 2020 - Wiley Online Library
With the development of communication systems, information securities remain one of the
main concerns for the last few years. The smart devices are connected to communicate …

Android malware detection techniques: A literature review

M Dhalaria, E Gandotra - Recent Patents on Engineering, 2021 - ingentaconnect.com
Objective: This paper provides the basics of Android malware, its evolution and tools and
techniques for malware analysis. Its main aim is to present a review of the literature on …

[PDF][PDF] Detecting malware families and subfamilies using machine learning algorithms: an empirical study

E Odat, B Alazzam, QM Yaseen - International Journal of …, 2022 - researchgate.net
Machine learning algorithms have proved their effectiveness in detecting malware. This
paper conducts an empirical study to demonstrate the effectiveness of selected machine …