🔭 Currently pursuing M.Tech in Information System Security Engineering at NIT Jamshedpur, where I bridge the worlds of secure systems and intelligent machines.
🌱 Passionate about all things Cybersecurity, Machine Learning, and Applied AI.
🧪 I love experimenting with:
- 🔐 Vulnerability detection & secure software design
- 🤖 AI-based solutions for real-world applications
- 🧠 Deep learning, NLP, and image recognition
🎓 Mentored under industry-grade training and real-time project work through internships and hackathons.
💬 Let’s collaborate if you're working on: ML for security, intelligent systems, or cool backend tools.
📫 Drop a mail at: sonalikumari6062@gmail.com
📺 Or catch my tutorials on YouTube: Code with Daisy
- Designed and implemented an advanced image encryption system leveraging chaotic maps (e.g., Logistic, Tent, or Henon maps) to generate highly secure, non-linear cryptographic keys.
- Integrated chaotic key generation with pixel-level transformations to encrypt images with high sensitivity, entropy, and resistance to brute-force and statistical attacks.
- Applied principles from information theory and cryptography to simulate and analyze system robustness for secure image transmission and storage.
- Explored information system assurance, secure coding practices, and cryptographic algorithm design in academic and applied settings.
- Intern @ The Sparks Foundation: Developed machine learning pipelines using Python, scikit-learn, and pandas, focusing on regression/classification tasks and model performance optimization.
- Built and trained CNN-based models for plant disease detection, integrating real-time image processing and predictive analysis into a user-friendly web platform.
- Developed an end-to-end ML-powered full stack application where users upload images of plant leaves through a web interface to:
- 🔍 Detect the disease,
- 💊 Display the cure, and
- 🛡️ Recommend preventive measures to avoid recurrence.
- Implemented data pipelines, data preprocessing, and visualization dashboards to monitor model behavior and performance metrics.
- Completed professional training in Automation Testing using Java and Selenium, improving QA efficiency for backend and ML-integrated systems.
- Designed automated test cases for web apps and model-serving interfaces, ensuring end-to-end functionality, data integrity, and user experience reliability.
- Built reusable test suites to simulate real-world user behavior and validate robustness across system components.
🛰️ Securing the future of image and video communication in an increasingly connected world.
This research explores cutting-edge techniques to make image and video transmission safer over potentially insecure networks. Our focus spans multiple dimensions of visual security:
- 🛡️ End-to-End Encryption for real-time visual data streams
- 🧠 AI-powered Tamper & Spoof Detection to identify unauthorized modifications
- 👁️🗨️ Visual Privacy Techniques — including transforming the data converted to unreadable format
- 📡 Secure Streaming Protocols with integrity verification and low-latency encryption
💡 Research Supervisor: [Prof. Alekha Kumar Mishra] 🏛️ Institution: National Institute of Technology (NIT), Jamshedpur
🧪 Department: Computer Science & Engineering
This work aims to build a foundation for trustworthy, private, and tamper-resistant visual communication across digital platforms.
- 🎓 Summer Trainee – ICT Academy, IIT Kanpur (C & C++)
- 💻 Automation Testing – Internshala (Java + Selenium)
- 🧠 GATE CS 2024 Qualified
- 🥇 1st Place (Agri Domain) – IEEE JU Hackathon 2021
- 🔥 Built and presented innovative ML systems at national-level competitions
- 🧠 Solved 180+ LeetCode Problems
- 🌍 Girlscript Scholar – Education Outreach Program
💡 "Engineering intelligent defenses-where AI meets cybersecurity"


