Integrating Opcode N-Grams and Word Embeddings for Enhanced Malware Classification: A Comparative Study with Transformer-Based Representations
This work proposes a comparative framework for malware classification that evaluates the synergy between traditional feature engineering and modern deep learning architectures. Our methodology follows two primary paths: first, we integrate opcode n-grams with word-embedding techniques (Word2Vec, Doc2Vec, and FastText)...