Aug 2026· Cluster Computing· Vol 29· 0 citations· 56 references
Computer Science
TL;DR
Experimental results demonstrate the superiority of HFE-DDL over the state-of-the-art method in vulnerability detection tasks and show that HFE-DDL has potential as a tool for proactively identifying vulnerabilities during development, aiming to produce more secure Android applications.
A dual-stream CodeBERT architecture is presented that addresses keyword bias —by combining pre-trained Transformer representations with a 50-dimensional hand-engineered security feature vector, supported by targeted data augmentation and two-stage adversarial fine-tuning.
Arjun Khurana, Talaya Farasat, Joachim Posegga et al.· 0 citations
This work proposes a unified malware detection framework that integrates Binary Improved Gravitational Search Algorithm for robust feature selection with Hidden Node Optimization (HNO) applied to an Extreme Learning Machine (ELM) classifier, making BIGSA-HNO-ELM a compelling solution for modern Android malware detectio...
Shouzab Khan, Muhammad Hassan· International journal for el...· 0 citations
HSF-Vul is proposed, a novel approach for software vulnerability detection and localization based on hierarchical semantic fusion that frame vulnerability detection as a binary classification task and extend it to line-level localization by analyzing the contribution of individual code lines.
Hong-Tao Wang, Xin Yang, Xiao-Feng Liu et al.· International Conference on...· 0 citations
The results demonstrate that the proposed adaptive framework substantially improves minority-class vulnerability detection, achieving up to a 2.5-fold increase in F1-score and up to 83% improvement in MCC compared to the no-imbalance baseline.
Fatma Altınsoy· Süleyman Demirel Üniversites...· 0 citations
FusionDroid is proposed, a lightweight multimodal Android malware detection framework that integrates permission-based static features, permission co-occurrence graph representations, and engineered runtime behavioral features through probability-level ensemble fusion that can improve Android malware detection while pr...
Experimental results show that AST-based structural features substantially improve recall compared with the TF-IDF baseline, while the combined TF-IDF and AST representation maintains this improved performance.
Vani Pasupula, M. N. V. Manikanth, Nagaraju Vassey· International Journal of Cre...· 0 citations
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