Cyber Security Projects and Work
A showcase of my cybersecurity work including SIEM operations, security dashboard development, machine learning threat detection, penetration testing, and cloud security implementations.
Monitored and triaged 20–50 SIEM alerts weekly at Workato, resolving Tier 1 incidents and documenting response actions to support the security team's incident management process. Implemented systematic alert prioritization and response protocols.
Reduced escalation workload for senior security team members through effective initial triage and comprehensive documentation
Designed and deployed 5+ Sigma dashboards leveraging Product Security Portal data, enabling real-time tracking of security bugs and issue trends. Created interactive visualizations for improved decision-making and security posture monitoring.
Cut report preparation time by 30%, streamlining security team workflows and enhancing visibility into security metrics
Conducted comprehensive packet analysis using Wireshark to capture and evaluate network traffic patterns, identifying potential security anomalies and protocol vulnerabilities. Analyzed TCP/IP communications and detected unusual traffic behaviors.
Network protocols, packet inspection, traffic pattern analysis, security anomaly detection, and forensic investigation techniques
Deployed AWS IAM policies, configured static websites with security best practices, and implemented load balancers to ensure secure and scalable cloud infrastructure. Established least-privilege access controls and multi-factor authentication.
AWS IAM, cloud security architecture, access control policies, infrastructure security, and secure deployment practices
Applied cybersecurity frameworks through academic projects including risk assessments with FAIR-U and Active Directory configuration in virtualized environments. Implemented Group Policy Objects and security hardening measures.
FAIR-U framework, risk quantification, Active Directory, security policy implementation, and enterprise identity management
Executed a full penetration test across a multi-host lab environment, simulating real-world attack scenarios from reconnaissance through exploitation. Used industry-standard tools to enumerate services, identify vulnerabilities, crack credentials, and exploit web application weaknesses. Delivered a formal report with prioritized remediation recommendations.
Vulnerability enumeration, exploitation, credential attacks, web app security testing, and professional findings documentation
Collaborated with a team of 5 to build a phishing URL detection model using the PhiUSIIL dataset. Applied Python (pandas, scikit-learn) for data preprocessing and feature selection, then trained and evaluated multiple classifiers — Logistic Regression, SVM, Decision Tree, Random Forest, and K-NN — to identify the most effective approach for detecting malicious URLs.
Feature engineering, model comparison, classification algorithms, dataset preprocessing, and team-based ML development
Analyzed 200,000 real banking transactions in Python and Google Colab to benchmark fraud detection approaches across three model architectures. Compared a traditional Logistic Regression baseline against a Multi-Layer Perceptron (MLP) and an LSTM recurrent network, evaluating trade-offs in accuracy, recall, and suitability for sequential financial data.
Deep learning, LSTM networks, imbalanced dataset handling, model benchmarking, and financial fraud pattern analysis