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cs.CR2026
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…
cs.CR2026
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…
cs.CR2026
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…