A review on feature selection in mobile malware detection
The widespread use of mobile devices in comparison to personal computers has led to a
new era of information exchange. The purchase trends of personal computers have started …
new era of information exchange. The purchase trends of personal computers have started …
Malicious application detection in android—a systematic literature review
Context: In last decade, due to tremendous usage of smart phones it seems that these
gadgets became an essential necessity of day-to-day life. People are using new …
gadgets became an essential necessity of day-to-day life. People are using new …
MTH-IDS: A multitiered hybrid intrusion detection system for internet of vehicles
Modern vehicles, including connected vehicles and autonomous vehicles, nowadays
involve many electronic control units connected through intravehicle networks (IVNs) to …
involve many electronic control units connected through intravehicle networks (IVNs) to …
Recurrent neural network model for IoT and networking malware threat detection
M Woźniak, J Siłka, M Wieczorek… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Security of networking in cyber-physical systems is an important feature in recent computing.
Information that comes to the network needs preevaluation. Our solution presented in this …
Information that comes to the network needs preevaluation. Our solution presented in this …
Constructing features for detecting android malicious applications: issues, taxonomy and directions
The number of applications (apps) available for smart devices or Android based IoT (Internet
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …
of Things) has surged dramatically over the past few years. Meanwhile, the volume of ill …
A three-step machine learning framework for energy profiling, activity state prediction and production estimation in smart process manufacturing
The dynamic nature of chemical processes and manufacturing environments, along with
numerous machines, their unique activity states, and mutual interactions, render challenges …
numerous machines, their unique activity states, and mutual interactions, render challenges …
[图书][B] Machine learning approaches in cyber security analytics
T Thomas, AP Vijayaraghavan, S Emmanuel - 2019 - Springer
This book introduces various machine learning methods for cyber security analytics. With an
overwhelming amount of data being generated and transferred over various networks …
overwhelming amount of data being generated and transferred over various networks …
K-means and alternative clustering methods in modern power systems
As power systems evolve by integrating renewable energy sources, distributed generation,
and electric vehicles, the complexity of managing these systems increases. With the …
and electric vehicles, the complexity of managing these systems increases. With the …
Spatial clustering and modelling for landslide susceptibility mapping in the north of the Kathmandu Valley, Nepal
In this article, we propose and test alternative sampling strategies based on clustering
distribution concepts to increase the efficiency of the landslide susceptibility model …
distribution concepts to increase the efficiency of the landslide susceptibility model …
Minimizing network traffic features for android mobile malware detection
A Arora, SK Peddoju - Proceedings of the 18th international conference …, 2017 - dl.acm.org
Smartphones have emerged as one of the dominant computing platforms in today's era
where Android has been the first choice for users as well as app developers due to its open …
where Android has been the first choice for users as well as app developers due to its open …