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 …

[PDF][PDF] Penta-NLP at EXIST 2024 Task 1–3: sexism identification, source intention, sexism categorization in tweets

FT Shifat, F Haider, M Sourove, DD Barua… - Working Notes of …, 2024 - ceur-ws.org
Social media platforms contains a vast user base and offers ease with which information can
be shared. This can adversely facilitate the spread of sexist content which is infeasible for …

FSSDroid: Feature subset selection for Android malware detection

N Polatidis, S Kapetanakis, M Trovati, I Korkontzelos… - World Wide Web, 2024 - Springer
Android malware has become an increasingly important threat to individuals, organizations,
and society, posing significant risks to data security, privacy, and infrastructure. As malware …

Multi-class Malware Detection via Deep Graph Convolutional Networks Using TF-IDF-Based Attributed Call Graphs

I Khan, YW Kwon - International Conference on Information Security …, 2023 - Springer
The proliferation of malware in the Android ecosystem poses significant security risks and
financial losses for enterprises and developers. Malware constantly evolves, exhibiting …

Security detection algorithm using CNN: Anomaly detection for API call sequence

J Chang, L Shi, Z Li, X Zuo… - Journal of Computational …, 2025 - journals.sagepub.com
This study proposes a security detection algorithm based on convolutional neural networks
(CNNs) to enhance anomaly detection in API call sequences, addressing the challenges of …

Classification of Android Malware from Binary Code Using Ensemble Method with Recursive Feature Elimination

N Tippayasem, K Piromsopa - 2024 21st International Joint …, 2024 - ieeexplore.ieee.org
In response to the burgeoning Android market and the concurrent proliferation of both
applications and malware, we propose a direct analysis approach to classify Android …

Feature-Driven Malware Detection using Cascade Machine Learning Models

A Mahato, R Majumdar, SK Ghosh - 2025 - researchsquare.com
Malware proliferation continues to jeopardize global data security and user privacy,
necessitating robust detection and classification mechanisms. In this research, we propose …

Using Artificial Intelligence in the Security of Cyber Physical Systems

ZG Aydın, M Kazanç - Alphanumeric Journal, 2023 - dergipark.org.tr
The prominence of cyber security continues to increase on a daily basis. Following the cyber
attacks in recent years, governments have implemented a range of regulations. The …

Malware Detection for Android TV

G Ozogur, MA Erturk, MA AYDIN - Available at SSRN 4766983, 2024 - papers.ssrn.com
Security of Android applications is a well-studied area in the literature but it is very limited for
other types of devices like Android TVs. Android TVs are growing in popularity with …