Ai-driven cybersecurity: an overview, security intelligence modeling and research directions

IH Sarker, MH Furhad, R Nowrozy - SN Computer Science, 2021 - Springer
Artificial intelligence (AI) is one of the key technologies of the Fourth Industrial Revolution (or
Industry 4.0), which can be used for the protection of Internet-connected systems from cyber …

Smart City Data Science: Towards data-driven smart cities with open research issues

IH Sarker - Internet of Things, 2022 - Elsevier
Cities are undergoing huge shifts in technology and operations in recent days, and 'data
science'is driving the change in the current age of the Fourth Industrial Revolution (Industry …

DroidMalwareDetector: A novel Android malware detection framework based on convolutional neural network

AT Kabakus - Expert Systems with Applications, 2022 - Elsevier
Smartphones have become an integral part of our daily lives thanks to numerous reasons.
While benefitting from what they offer, it is critical to be aware of the existence of malware in …

SEDMDroid: An enhanced stacking ensemble framework for Android malware detection

H Zhu, Y Li, R Li, J Li, Z You… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The popularity of the Android platform in smartphones and other Internet-of-Things devices
has resulted in the explosive of malware attacks against it. Malware presents a serious …

Jucify: A step towards android code unification for enhanced static analysis

J Samhi, J Gao, N Daoudi, P Graux, H Hoyez… - Proceedings of the 44th …, 2022 - dl.acm.org
Native code is now commonplace within Android app packages where it co-exists and
interacts with Dex bytecode through the Java Native Interface to deliver rich app …

A survey and evaluation of android-based malware evasion techniques and detection frameworks

P Faruki, R Bhan, V Jain, S Bhatia, N El Madhoun… - Information, 2023 - mdpi.com
Android platform security is an active area of research where malware detection techniques
continuously evolve to identify novel malware and improve the timely and accurate detection …

Android malware detection as a bi-level problem

M Jerbi, ZC Dagdia, S Bechikh, LB Said - Computers & Security, 2022 - Elsevier
Malware detection is still a very challenging topic in the cybersecurity field. This is mainly
due to the use of obfuscation techniques. To solve this issue, researchers proposed to …

Coevolution of mobile malware and anti-malware

S Sen, E Aydogan, AI Aysan - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Mobile malware is one of today's greatest threats in computer security. Furthermore, new
mobile malware is emerging daily that introduces new security risks. However, while existing …

The rise of obfuscated Android malware and impacts on detection methods

WF Elsersy, A Feizollah, NB Anuar - PeerJ Computer Science, 2022 - peerj.com
The various application markets are facing an exponential growth of Android malware. Every
day, thousands of new Android malware applications emerge. Android malware hackers …

A multi-model ensemble learning framework for imbalanced android malware detection

H Zhu, Y Li, L Wang, VS Sheng - Expert Systems with Applications, 2023 - Elsevier
The continuous malicious software (malware) attacks on smartphones pose a serious threat
to the security of users, especially the dominant platform Android. Data-driven methods …