[A-18-4] 自然言語処理と機械学習を用いた詐欺メールの判定
この講演はキャリアエクスプローラーの掲載を希望しています。
キーワード：電子メールの分類、機械学習、自然言語処理、感情分析、サイバーセキュリティ
Due to its ease of use, speed, adaptability, and ability to keep a complete record of correspondence, email is a commonly used and trusted communication medium. The vulnerability of these emails to cyberattacks has increased. This study utilized the hybrid-based sentiment analysis approach for email fraud detection. The lexicon-based using the Word2Vec feature and Machine Learning (ML) classification approach using both the Bag of Words and TF-IDF feature extraction techniques were adopted to optimize accuracy. The Machine Learning classifiers adopted are Multilayer Perception, Decision Tree, Random Forest, KNN, SVM, and logistic model.
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