Background
Education
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Paper: A Novel Approach for Detecting Forged SMTP Headers using Deep Learning and Synthetic Data Generation
Accepted in the Main Track of SBSeg 2025, Brazil’s premier cybersecurity symposium, achieving the maximum distinction (Four Seals of Approval).
- Excellence: One of the select few papers to receive all four approval seals, validating its technical depth and innovation.
- Innovation: Proposed a new architecture combining Deep Learning and Synthetic Data to detect sophisticated phishing attacks.
- Recognition: Derived from my undergraduate thesis and presented in person in Foz do Iguaçu, representing CEFET/RJ.
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A comprehensive engineering degree bridging hardware and software. The curriculum demanded rigor in algorithms, data structures, operating systems, and computer architecture.
- Focus: Built a strong theoretical foundation in problem-solving and systems design.
- Application: Developed practical experience through complex academic projects involving embedded systems and low-level programming.