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Semantic Detection of Targeted Attacks Using DOC2VEC Embedding
2021
Journal of Communications Software and Systems
The targeted attack is one of the social engineering attacks. The detection of this type of attack is considered a challenge as it depends on semantic extraction of the intent of the attacker. However, previous research has primarily relies on the Natural Language Processing or Word Embedding techniques that lack the context of the attacker's text message. Based on Sentence Embedding and machine learning approaches, this paper introduces a model for semantic detection of targeted attacks. This
doi:10.24138/jcomss-2021-0113
fatcat:ozfnk4mgwzgjlhqtaffcsvc2k4