Security and privacy in IoT using machine learning and blockchain: Threats and countermeasures

N Waheed, X He, M Ikram, M Usman… - ACM computing …, 2020 - dl.acm.org
Security and privacy of users have become significant concerns due to the involvement of
the Internet of Things (IoT) devices in numerous applications. Cyber threats are growing at …

Machine and deep learning for iot security and privacy: applications, challenges, and future directions

S Bharati, P Podder - Security and communication networks, 2022 - Wiley Online Library
The integration of the Internet of Things (IoT) connects a number of intelligent devices with
minimum human interference that can interact with one another. IoT is rapidly emerging in …

Malware detection in mobile environments based on Autoencoders and API-images

G D'Angelo, M Ficco, F Palmieri - Journal of Parallel and Distributed …, 2020 - Elsevier
Due to their open nature and popularity, Android-based devices represent one of the main
targets for malware attacks that may adversely affect the privacy of their users. Considering …

Malicious application detection in android—a systematic literature review

T Sharma, D Rattan - Computer Science Review, 2021 - Elsevier
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 …

[HTML][HTML] Obfuscapk: An open-source black-box obfuscation tool for Android apps

S Aonzo, GC Georgiu, L Verderame, A Merlo - SoftwareX, 2020 - Elsevier
Obfuscapk is an open-source automatic obfuscation tool for Android apps that works in a
black-box fashion (ie, it does not need the app source code). Obfuscapk supports advanced …

Effective classification of android malware families through dynamic features and neural networks

G D'Angelo, F Palmieri, A Robustelli… - Connection …, 2021 - Taylor & Francis
Due to their open nature and popularity, Android-based devices have attracted several end-
users around the World and are one of the main targets for attackers. Because of the …

Feature subset selection for malware detection in smart IoT platforms

J Abawajy, A Darem, AA Alhashmi - Sensors, 2021 - mdpi.com
Malicious software (“malware”) has become one of the serious cybersecurity issues in
Android ecosystem. Given the fast evolution of Android malware releases, it is practically not …

RealMalSol: real-time optimized model for Android malware detection using efficient neural networks and model quantization

M Chaudhary, A Masood - Neural Computing and Applications, 2023 - Springer
Android is currently the most dominant platform in the market in comparison with all other
operating systems (OS) such as iOS, Windows, and Blackberry. As the scope of Android …

A federated approach to Android malware classification through Perm-Maps

G D'Angelo, F Palmieri, A Robustelli - Cluster Computing, 2022 - Springer
In the last decades, mobile-based apps have been increasingly used in several application
fields for many purposes involving a high number of human activities. Unfortunately, in …

A comprehensive review on permissions-based Android malware detection

Y Sharma, A Arora - International Journal of Information Security, 2024 - Springer
The first Android-ready “G1” phone debuted in late October 2008. Since then, the growth of
Android malware has been explosive, analogous to the rise in the popularity of Android. The …