Email-Based Privilege Escalation Attack Detection in Cloud Environments Using Machine Learning

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Author(s): B. Sreedevi (SASTRA University, India)and S. Barathi (Srinivasa Ramanujan Centre, India)
Copyright: 2026
Pages: 26
Source title: Policies Against Fraud and Cybercrime: Strategic, Legal, and Technological Approaches
Source Author(s)/Editor(s): Ricardo Marcão (ISLA Santarem, Polytechnic University, Portugal & NECE, University of Beira Interior, Portugal ), Vasco Ribeiro Santos (ISLA Santarém, Portugal & GOVCOPP, Portugal)and Nuno Mateus-Coelho (CTS UNINOVA, Portugal & Lusófona University, Portugal)
DOI: 10.4018/979-8-3373-5992-2.ch004

Keywords: Computer Science & IT / Cyber and Network Security / Information Science Reference / IT Policy & Standardization

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Abstract

Cloud computing offers scalable data access and operational efficiency but introduces serious security challenges—most notably, privilege escalation attacks where insiders gain unauthorized administrative control. This project presents a machine learning-based system to detect such attacks through email analysis. Email content is transformed into numerical features using vectorization techniques. Several classifiers including Random Forest, KNN, SVM, XGBoost, and LightGBM are trained on a labeled dataset to differentiate between safe and malicious emails. An ensemble voting classifier ensures higher accuracy and reduces false positives. The system performs real-time detection and generates alerts for suspicious activities, thereby enhancing cloud security against internal threats.

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Email-Based Privilege Escalation Attack Detection in Cloud Environments Using Machine Learning

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