Hi, I'm Deepan Chandru

SOC Analyst & Cybersecurity Professional

Dedicated to securing digital systems and responding to security threats. Specializing in threat detection, incident response, security monitoring, and network security analysis with expertise in SOC operations and security investigations.

Contact Me View Projects

About Me

I'm a dedicated cybersecurity professional with a strong foundation in computer science and engineering. Having completed my Bachelor's degree at SRM Institute of Science and Technology, Chennai, I specialize in threat detection, incident response, and security operations management.

With expertise in both defensive security operations and offensive security techniques, I work on monitoring security systems, analyzing threats, and implementing incident response procedures. My experience includes security event analysis, threat investigation, network monitoring, and security auditing.

I'm passionate about staying updated with the latest cybersecurity trends and threat landscapes, always eager to tackle new challenges in the ever-evolving digital security environment.

SOC Analyst

Threat Analyst

Education

SRM Institute of Science and Technology, Chennai

Bachelor of Technology in Computer Science and Engineering

Specialization in Cybersecurity

September 2021 - June 2025

Skills & Technologies

Cybersecurity

Network Security

Penetration Testing

Ethical Hacking

Security Auditing

Incident Response

Cryptography

SOC Operations

Threat Detection

Log Analysis

Network Monitoring

Security Events Analysis

Alert Triage

Forensic Analysis

Vulnerability Management

Malware Analysis

SIEM Monitoring

IDS/IPS

Languages & OS

Python

Linux

Windows

Security Tools

Wireshark

Nmap

Wazuh

Suricata

Splunk

Sysmon

PE Studio

Git

Data Analytics & AI

Power BI

RAG (Retrieval Augmented Generation)

Security Frameworks

MITRE ATT&CK

Featured Projects

Real-Time Phishing URL Detection Using Ensemble Learning

Built a Python system that can analyze 10,000 URLs per minute to detect phishing attempts in real-time email streams, reducing successful phishing attacks by 8.6%.
Created an advanced machine learning system using multiple algorithms (Random Forest, XGBoost, CatBoost) that improved detection accuracy by 19% compared to traditional methods.
Analyzed over 50,000 suspicious URLs to identify hidden patterns and improve detection capabilities by 22%.
Worked with security experts to fine-tune the system, reducing false alarms by 15% while maintaining high detection rates.

Python Scikit-learn XGBoost CatBoost Ensemble Learning

Supervised Polarity Classification of Tweets Using NLP

Cleaned and prepared 1.6 million tweets for analysis using NLTK and SpaCy to ensure high-quality data.
Built sentiment analysis models using Logistic Regression and Random Forest, achieving 90% accuracy - 30% better than simple keyword-based methods.
Made the system fast enough to analyze sentiment in real-time, responding in under 200 milliseconds for large datasets.
Built an interactive dashboard with Streamlit to show sentiment trends, helping teams understand data 40% faster.
Tested the model thoroughly to ensure it works well with different types of Twitter content, making predictions 22% more stable.

Python NLTK SpaCy Scikit-learn Streamlit NLP

Professional Experience

SOC Analyst Trainee

IARM

March 2026 - Current

Engaged in comprehensive SOC operations training with hands-on experience in threat detection, incident response, and security monitoring. Analyzing security events, performing alert triage, and implementing response procedures under guidance of senior security professionals.

Data Science Intern

Gradtwin

February 2025 - April 2025

Worked on foundational data science projects including data cleaning, exploratory data analysis, and basic machine learning model development. Gained practical experience in data visualization, statistical analysis, and data-driven decision making.