Security analysis of IoT devices by using mobile computing: a systematic literature review
Internet of Things (IoT) devices are operating in various domains like healthcare
environment, smart cities, smart homes, transportation, and smart grid system. These …
environment, smart cities, smart homes, transportation, and smart grid system. These …
Security in Internet of Things: A review
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 …
connected multimedia devices. It has dragged the attention of the community because it …
An efficient approach for phishing detection using machine learning
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 …
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 …
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 …
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
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 …
infrastructure, facilities, networks and systems. Static analysis is an effective approach to …
Malware detection using machine learning algorithms for windows platform
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 …
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
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 …
main concerns for the last few years. The smart devices are connected to communicate …
Android malware detection techniques: A literature review
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 …
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 …
paper conducts an empirical study to demonstrate the effectiveness of selected machine …