arXiv:2608. 16334v1 Announce Type: new Abstract: Keystroke dynamics (typing patterns) can be used as a behavioural biometric modality for user authentication, with applications such as fraud prevention.
By Nuwan Kaluarachchi, Sevvandi Kandanaarachchi, Kristen Moore, Arathi Arakala, Conrad Sanderson
arXiv:2608. 17659v1 Announce Type: cross Abstract: LLM-powered GUI agents that autonomously operate smartphones are rapidly transitioning from research prototypes to early real-world deployment.
By Sujin Chen, Lijun Li, Tianyi Du, Jing Shao
arXiv:2605. 09028v3 Announce Type: replace Abstract: Machine learning-based Android malware detectors often fail in real-world deployment due to domain shift, where models trained on one data source perform poorly on applications from another.
By Md Rafid Islam
arXiv:2607. 11649v1 Announce Type: cross Abstract: Network-based anomaly detection for IoT devices has matured to the point of reporting strong detection accuracy, yet most published systems stop at raising an alert and leave the question of automated enforcement to future work or to a programmable data plane that few real networks operate.
By Muhammet Emir Korkmaz, Kemal Bicakci, Yusuf Uzunay
arXiv:2608. 19938v1 Announce Type: cross Abstract: Existing approaches to anomalous behaviour log detection, such as Wazuh rely primarily on predefined detection rules, while statistical anomaly detection approaches such as OpenSearch identify deviations from previously observed behavioural patterns.
By Christopher Henshaw, Gour Karmakar
arXiv:2608. 14826v1 Announce Type: cross Abstract: The wireless networks have historically faced significant security vulnerabilities, necessitating advanced anomaly detection mechanisms, especially as networks evolve towards 6G and beyond.
By Nurullah Aksu, Ali Fuat Sahin, Semiha Tedik Ba\c{s}aran