Obbu Venkata Sai Nithin

• Project: Trojan Horse Malware Detection Using Machine Learning
• Developed a robust machine learning model to detect Trojan Horse malware. Utilized advanced algorithms to analyze system behavior, network traffic, and file attributes, enabling real-time identification of malicious software disguised as legitimate programs its a 3 layer model.
• Layer 1 - Statistical Signature-Based Detection: • Identifies pre-existing virus signatures efficiently. • Converts files to bytecode and matches them with a known malware dataset. • Acts as the initial defense against non-morphed viruses.
• Layer 2 - Optimized Meta Neural Deep Learning: • Defines parameters for Trojan detection. • Utilizes a randomized feature extraction algorithm to introduce unpredictability. • Incorporates a shadowed dataset for privacy and parameter impact analysis using explainable AI libraries.
• Layer 3 - Probability Analysis and Anomaly Detection: • Evaluates the probability of a virus being present. • Utilizes probability parameter plots for further analysis. • Activates anomaly detection, including sandbox analysis, for high-probability cases. • Requires substantial computational resources, activated selectively based on predetermined thresholds.
• Currently writing a research paper about this.

• Simulated how hydrogen atom looks in its ground state and its shapes(s,p,d,f) were represented using blender.
• Scripts were written using blender python.
• Dealt with double differential time independent Schrodinger equation to obtain solutions.
• Used Numerov algorithm to approximate solutions.
• Currently working to publish a research paper along with Mr Karthik Sasthry .

Engineering Resources Hub PWA

• Developed a Progressive Web Application (PWA) designed to serve as a comprehensive resource hub for engineering students, featuring collaborative tools, study materials, and event notifications. The application includes:
• Course Material Repository: Centralized platform for uploading and accessing lecture notes, textbooks, and past exam papers.
• Collaborative Tools: Implemented a discussion forum and real-time chat feature using WebSockets, enabling students to collaborate on projects and assignments effectively.
• Personalized Dashboard: Developed a personalized dashboard using React, allowing students to track their progress, manage deadlines, and receive customized notifications.
• Offline Access: Enabled offline access through service workers, ensuring uninterrupted access to study materials and notes.
• Frontend: React, HTML5, CSS3, JavaScript (ES6+)
• Backend: Node.js, Express.js
• Database: MongoDB
• Others: Service Workers, OAuth 2.0, Push Notifications

• Completed comprehensive training in cloud computing, gaining expertise in relevant topics.
• Learnt about cloud computing models, deploying them and virtualization techniques.
• Learnt about different cloud service providers and their architecture and design
• Used metrics to monitor application and infrastructure performance.

• GPA/CGPA :9.14 (As of 3rd semester)
• CODING CLUB: Core team member
• Member of IUCEE SPARK PROGRAM

• Final Grade: 95%

• Final Grade: 94%