4 papers · 1 filter
What Malware Actually Does: An Empirical Analysis of Post-Infection Behavior Across Malware Families
Emmanuela Andam, Emanuel S. Grant, Naima Kaabouch
Most malware detection research focuses on identifying whether a file is malicious before it executes. Far less attention goes to what happens after infection. This paper presents…
Benchmarking Classical and Quantum Machine Learning for Intrusion Detection Across Multiple Datasets
Taha M. Mahmoud, Naima Kaabouch
Intrusion detection is examined through a comparative benchmark of classical and quantum machine learning models on three datasets: NSL-KDD, UNSW-NB15, and MQTTEEB-D2025. The analy…
A Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders
Emmanuela Andam, Yasir Abbas Zaidi, Abdelali Hadir +2
Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are typically launched through phis…
A Structured State Space Sequence Model for Multi-Class Classification of Malware
Emmanuela Andam, Rana Shaaban, Emanuel Grant +1
By 2030, Internet of Things (IoT) devices are projected to reach 40 billion, with fast-paced technological advancements in fields such as industry, healthcare, agriculture, automob…