This research project aimed to quantitatively evaluate the effectiveness of popular ad blockers in enhancing user privacy and improving browser performance across major web browsers.

Implemented a Python algorithm for efficient extraction of JPEG, PNG, and PDF files from large hexadecimal dump files, providing results in under 20 seconds. Achieving an 80% improvement over manual extraction.

Exploited BuggyWebApplication to identify and attack a wide range of web application vulnerabilities, including OWASP Top 10 and meticulously documented remediation strategies for a comprehensive security assessment.

Analysis of Reentrancy Attack Vulnerabilities in Smart Contracts. This project consists of CryptoMask (wallet) and Intruder's Smart Contract, demonstrating exploitation of vulnerabilities in CryptoMask and securing it.

Python-based OCR solution to extract text from PDF contracts, enhancing text recognition accuracy by 40% and enabling faster data extraction for contract analysis in a telecommunications R&D environment.

Automated data pipeline using Python, AWS Lambda, and Athena to extract key fields from large JSON files reducing manual data processing time by 60% and improving data accessibility.

Designed and implemented a complete data pipeline on AWS to protect sensitive customer viewing data while still enabling useful business insights for a Dish Network-like environment to analyze regional viewing trends without exposing individual habits.