Most corporate workplace environments enforce policies and technical controls that limit the storage of sensitive data on client endpoints. Consequently, ransomware operators have evolved variants that expand their attack surface from local systems to network drives and shared storage resources.
arXiv:2610.01949v1 Announce Type: cross
Abstract: Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are...
By Emmanuela Andam, Yasir Abbas Zaidi, Abdelali Hadir, Emmanuel Grant, Naima Kaabouch
The paper introduces a Cost-Aware Hierarchical Multi-Agent System (HMAS) for ransomware detection and family attribution that adaptively selects analysis modalities to balance accuracy and computational cost. Static analysis is used first, with dynamic and memory modalities added only when confidence is low or specialist agents disagree, guided by a cost model. Experiments show HMAS achieves high accuracy (96.57% binary detection, 0.90 macro‑F1 attribution) while reducing analysis cost by 43.97% and latency, with 56.05% of cases resolved using static evidence alone.
By Mubashar Iqbal, Asifullah Khan
The paper presents a lightweight machine‑learning approach for multi‑class malware detection on resource‑constrained devices. Using a LightGBM classifier with SMOTE oversampling, SOM‑US undersampling, and Genetic‑Algorithm feature selection, the authors achieve 89.1 % accuracy on four malware families and 76 % on 16 individual malware types. A second Random‑Forest model further improves family classification to 91.2 % and individual classification to 78.7 %.
By Abdul Khalek Alve, Alif Rahman, Saadman Zaman, Sazzad Hossen Himel, Muhammad Iqbal Hossain
arXiv:2609.21303v1 Announce Type: cross
Abstract: Product abuse is an individually rare, but growing, problem across the SaaS industry. Highly sophisticated threat actors can misuse security platform...
By Shaefer Drew, Michael Brautbar, Paul Knight, Edward Raff, Lana Peric-McDermott, Simran Sarin, Nickolas Machado, Hanna Albright, Vitaly Zaytsev
arXiv:2610.01893v1 Announce Type: cross
Abstract: By 2030, Internet of Things (IoT) devices are projected to reach 40 billion, with fast-paced technological advancements in fields such as industry, h...
By Emmanuela Andam, Rana Shaaban, Emanuel Grant, Naima Kaabouch