Projects
Intelligent SMS Evidence Classification Framework for Mobile Forensics
SMS Evidence Analysis
Intelligent SMS Evidence Classification Framework for Mobile Forensics - by Elaine Fernandes
XAI-DSS Pipeline
Intelligent SMS Evidence Classification Framework for Mobile Forensics - by Elaine Fernandes
Classification Results
Intelligent SMS Evidence Classification Framework for Mobile Forensics - by Elaine Fernandes
Model Training Process
Intelligent SMS Evidence Classification Framework for Mobile Forensics - by Elaine Fernandes
Project Workflow & Plan
I developed an Explainable AI Decision Support System (XAI-DSS) for SMS-based mobile phone forensics. The framework classifies SMS evidence as suspicious or non-suspicious using machine learning techniques, including TF-IDF, Logistic Regression, and Random Forest. A key focus of the project was explainability, allowing investigators to understand why predictions were made through confidence scores and feature analysis. The system supports forensic transparency, legal defensibility, and structured reporting while helping reduce the manual workload required to analyze large volumes of SMS evidence.
https://www.linkedin.com/in/elaine-fernandes-108560245/
https://github.com/elaine-fernandes/Demo
https://elainefernandesportfolio.lovable.app/#home
Type of employment sought
Cyber Security Analyst, Digital Forensics Analyst, SOC Analyst, Threat Intelligence Analyst, or AI Security Research roles focused on cybersecurity, digital investigations, and secure AI systems.
Areas available to work
London, United Kingdom, with openness to hybrid or remote opportunities across the UK.
Contact Elaine