Headline

Cybersecurity Enthusiast | Network Security • Vulnerability Assessment • Ethical Hacking | SIEM • Nmap • Wireshark | CCST Aspirant

About

Cybersecurity enthusiast with hands-on experience in network security, vulnerability assessment, and threat analysis. Skilled in tools such as Nmap and Wireshark, with practical exposure through cybersecurity simulations and real-world projects. Developed a federated learning-based anomaly detection system for IoT networks, focusing on secure and privacy-preserving threat detection. Currently exploring advanced concepts like Zero Trust architecture, intrusion detection systems, and cloud security. Actively seeking opportunities to apply my skills and grow as a cybersecurity professional.

Location

Gurugram

Work experience

Solutions Architecture – Job Simulation at Amazon Web Services (Forage), Jan 2026 - Apr 2026 · 4 mos, Remote, Completed a cloud architecture simulation focusing on designing secure and scalable systems. • Designed cloud-based architecture using AWS services • Applied best practices for system security and scalability • Implemented cost optimization strategies • Gained understanding of cloud security principles

Cybersecurity Analyst – Job Simulation at Tata Consultancy Services (Forage), Jan 2026 - Apr 2026 · 4 mos, Remote, Completed a cybersecurity analyst job simulation involving real-world security scenarios. • Performed Identity and Access Management (IAM) strategy assessment • Identified security gaps and proposed mitigation strategies • Analyzed access control systems and risk factors • Gained practical exposure to cybersecurity frameworks and security analysis

Federated Learning-Based Malware & Anomaly Detection for IoT Networks (Cybersecurity Project) at Academic Team Project, Jan 2026 - Apr 2026 · 4 mos, Remote, Developed a federated learning-based intrusion detection system for securing IoT networks as part of a collaborative team project. • Collaborated in a team of 2 to design and implement a distributed anomaly detection system • Contributed to building machine learning models for detecting malware and anomalous network behavior • Applied federated learning techniques to ensure data privacy across decentralized nodes • Analyzed cyber threats such as botnet activity, unauthorized access, and DDoS attacks • Evaluated model performance using confusion matrix, precision, recall, and F1-score • Visualized results using heatmaps, histograms, and anomaly score distributions

Student at K.R. Mangalam University, Aug 2023 - Apr 2026 · 2 yrs 9 mos, Gurugram, Haryana, India

Education

Bachelor of Science (B.Sc), Cybersecurity, K.R. Mangalam University

Non-Medical, Army Public School Kaluchak