Crypto-ransomware: A revision of the state of the art, advances and challenges

JA Gómez Hernández, P García Teodoro… - Electronics, 2023 - mdpi.com
According to the premise that the first step to try to solve a problem is to deepen our
knowledge of it as much as possible, this work is mainly aimed at diving into and …

[HTML][HTML] Android Malware Detection and Identification Frameworks by Leveraging the Machine and Deep Learning Techniques: A Comprehensive Review

SK Smmarwar, GP Gupta, S Kumar - Telematics and Informatics Reports, 2024 - Elsevier
The ever-increasing growth of online services and smart connectivity of devices have posed
the threat of malware to computer system, android-based smart phones, Internet of Things …

Medicinal Plant Classification Using Particle Swarm Optimized Cascaded Network

MT Islam, W Rahman, MS Hossain, K Roksana… - IEEE …, 2024 - ieeexplore.ieee.org
Medicinal plants are essential to healthcare since ancient times and are integral to
developing drugs and other medical treatments. More than 25% of medicines in developed …

Gauss-mapping black widow optimization with deep extreme learning machine for android malware classification model

G Aldehim, MA Arasi, M Khalid, SS Aljameel… - IEEE …, 2023 - ieeexplore.ieee.org
Nowadays, the malware on the Android platform is found to be increasing. With the
prevalent use of code obfuscation technology, the precision of antivirus software and …

Android ransomware detection using supervised machine learning techniques based on traffic analysis

A Albin Ahmed, A Shaahid, F Alnasser, S Alfaddagh… - Sensors, 2023 - mdpi.com
In today's digitalized era, the usage of Android devices is being extensively witnessed in
various sectors. Cybercriminals inevitably adapt to new security technologies and utilize …

Android ransomware detection using a novel hamming distance based feature selection

HH Rahima Manzil, SM Naik - Journal of Computer Virology and Hacking …, 2024 - Springer
Ransomware is a serious cyberthreat for Android users, with devastating consequences for
its victims. By locking or encrypting the targeted device, victims are often left unable to …

Prediction of android ransomware with deep learning model using hybrid cryptography

KR Kalphana, S Aanjankumar, M Surya… - Scientific Reports, 2024 - nature.com
In recent times, the number of malware on Android mobile phones has been growing, and a
new kind of malware is Android ransomware. This research aims to address the emerging …

ARdetector: Android ransomware detection framework

D Li, W Shi, N Lu, SS Lee, S Lee - The Journal of Supercomputing, 2024 - Springer
Ransomware has affected a broad range of public and private-sector organizations, and the
impacts include direct and indirect financial loss (eg, opportunity costs), reputational …

Lightweight Crypto-Ransomware Detection in Android Based on Reactive Honeyfile Monitoring

JA Gómez-Hernández, P García-Teodoro - Sensors, 2024 - mdpi.com
Given the high relevance and impact of ransomware in companies, organizations, and
individuals around the world, coupled with the widespread adoption of mobile and IoT …

Meta-SonifiedDroid: Metaheuristics for Optimizing Sonified Android Malware Detection

P Tarwireyi, A Terzoli, MO Adigun - IEEE Access, 2024 - ieeexplore.ieee.org
To mitigate the rising threat of Android malware, researchers have been actively looking for
mechanisms that will enable rapid and accurate malware detection. Recently, attention has …