AI-Powered IDS
Machine learning-assisted intrusion detection using flow data, anomaly detection, and attack classification.
SOC Operations • Digital Forensics & Incident Response • Detection Engineering
Available for: SOC Internships • DFIR Internships • Security Engineering Internships
Building practical cybersecurity projects focused on digital forensics, incident response, threat hunting, detection engineering, and security automation.
I'm Julian Silva-Erazo, a Computer Science & Information Security student at John Jay College of Criminal Justice focused on SOC Operations, Digital Forensics & Incident Response (DFIR), Detection Engineering, and Security Automation.
Through hands-on projects, research, and lab environments, I've worked on intrusion detection systems, threat intelligence automation, and forensic investigation workflows. Silvanyx serves as my platform for cybersecurity projects, technical research, and future security tools.
Hands-on cybersecurity projects built from real-world SOC, DFIR, and security engineering workflows.
Machine learning-assisted intrusion detection using flow data, anomaly detection, and attack classification.
Automated relevance scoring pipeline using LLMs, enrichment logic, and structured alert triage.
Forensic analysis of Windows artifacts, browser activity, USB evidence, timestamps, and investigation timelines.
Future DFIR timeline builder for forensic artifacts, evidence tracking, timestamps, and investigation notes.
Tools, platforms, and technologies leveraged for security operations, digital forensics, threat detection, and security automation.
View my resume showcasing experience in security operations, digital forensics, detection engineering, security automation, and cybersecurity research.
Open to cybersecurity internships, SOC analyst opportunities, DFIR projects, and security engineering collaborations.