SREERAM GR

Pursuing Master of Science in Cybersecurity, Technology and Policy at University of Texas at Dallas from August 2024 seeking internship opportunities

A masters student specialising in cybersecurity, driven by a passion to learn and excel in the field. I constantly seek new opportunities to expand my skills

• Successfully detected and mitigated network intrusions and DDoS attacks using TATA Arbor and NTT Arbor systems, reducing potential downtime by 25%
• Strengthened endpoint security across the organization by implementing and managing fortiEDR and Cortex XDR, leading to a reduction in endpoint incidents by 20%
• Resolved over 150 incident and request tickets via ServiceNow, improving response time by 25% and enhancing overall service delivery.
• Gained expertise in IBM Qradar (SIEM) and Cyware (SOAR), optimizing security event management processes and decreasing false positives by 15%.
• Enhanced application security by deploying and managing F5 Silverline WAF, resulting in 20% fewer web-based security incidents
• Effectively utilized Z-scalar reconnaissance tool (honeypot) to detect and prevent cyberattacks, improving threat detection rates by 25%

• Certified Ethical Hacker, EC Council
• Certified Cloud Security Knowledge (CCSK) V4
• Palo Alto Networks Micro-Credential for Cortex XDR Support Engineer
• Certified Forti-EDR Analyst

Title: Fake News Detection using Machine Learning
Duration: Feb - Jun ’22
Team size: 4
Summary: The main objective of the project was to identify bogus news; it involved finding straightforward solutions to a traditional text classification problem, building a model that could distinguish between ‘real’ and ‘fake’ news; this was accomplished via application of NLP (Natural Language Processing) techniques that identified ‘fake’ or inaccurate news reports originating from unreliable sources and turning them into real news
Individual Role: Team presenter, worked on slides in PowerPoint, developing ideas

Nationality: Indian