Authors: Dileep Chandra Mouli, Mrs.D.Sudha M.E

Abstract: Today Cyberattack are heavily automated, relying on AI based intrusion methods and fast evolving malware to evade network defense mechanisms. Static honeypots are used for threat monitoring, but they can be quickly identified by professional attackers, limiting their usefulness in practice. This work develops an AI-Powered Polymorphic Honeypot (AIPPH), which facilitates adaptive, intelligent, and stealthy threat deception for advanced network security systems. The above- mentioned approach integrates machine-learning-based behavioral analysis, dynamic environment generation, and polymorphic service emulation for the honeypot to evolve all its system signatures, network behavior, responses, and operating- system-level characteristics in real time. This flexibility greatly improves engagement times by attackers and minimizes the risk of honeypot detection. A real-time threat intelligence module deepens the capabilities of the system by clustering attacker behavior and discovering previously unknown zero-day attacks.

Published by: vikaspatanker

Authors: Tellakula Bhuvana Sai Ram, Patteparapu Kethana Lakshmi, Shaik Baji Shareef, Kuchu Karthik Naidu, A. V. S. Sudhakar Rao

Abstract: In today’s digital era, access to quality learning resources is often limited by financial constraints and lack of personalized guidance. Traditional online learning platforms primarily follow a one-way knowledge delivery model, which restricts real-time interaction and collaborative growth. This paper presents Peer Skill, a credit-based peer-to-peer skill exchange platform that enables users to both learn and teach skills without any monetary transactions. The platform introduces a unique credit point mechanism, where users earn credits by teaching skills and spend them learning new ones. The system incorporates session booking, teacher approval workflows, real-time virtual classes using video conferencing tools, and a feedback-based rating system to ensure quality learning experiences. Additionally, users can apply to become teachers through an admin-controlled verification process involving interviews.

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Authors: Dr C Chinna Suresh Babu, S.Kamruddin

Abstract: Andhra Pradesh is called as the “Rise Bowl” of India, Andhra Pradesh consists of 13 districts. Out of these 13 districts Y.S.R Kadapa (nearst while Kadapa) District has lots of mineral resources ,irrigation projects, Cement and Uranium Industries and well known for Turmeric ,Paddy and Red Gram crops as well as Historical places like Gandikota etc., In this Project weare going to deal with only the Irrigational Structures or Projects in Kadapa District like how many Major, Minor, Medium Irrigational works, at what extent they are helping Kadapa District, About Ongoing Irrigation and also about Water work’s or Projects, about rivers flowing in Kadapa District. The present study will provide a clear-cut information about the irrigation profile of the entire YSR with emphasis on major and minor irrigation structures and networks which will provide an overall glimpse to the district which will helpful to the future studies and common man also. Introduction Y.S.R. Kadapa district lies in the Rayalaseema region and experiences low rainfall (~700 mm annually). The district depends heavily on irrigation systems such as canals, reservoirs, and groundwater. Despite having major irrigation projects like K.C Canal and Telugu Ganga Project, large areas still face water scarcity.

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Authors: Thilak Patel, Bharath, Abhiram, Vamshi

Abstract: Budget Mate is an online expense tracker that offers smart finance management using machine learning. Users can input or extract expense and classify it by categories such as utilities, groceries, housing, entertainment, and subscription services. The machine learning based classification requires little manual input, while increasing the fidelity of managing and tracking finance. Users can track monthly expenses, analyze spending patterns, and reflect on their financial behaviors through interactive data visualization on a user dashboard. Furthermore, Budget Mate provides users with insight into a potential money management source that is smarter than tracking money—it provides solid budget plans, and savings recommendations based on any user behavior, which could encapsulate historical expense data, conversation note, and even some higher level personal finance inquires, potentially expanding to a method of money management beyond expense tracking and giving a proactive form of money management. Using a unified simplified interface, the service can scale beyond simple expense, and can seriously accommodate divergent scenarios.

DOI: https://doi.org/10.5281/zenodo.19366908

 

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Authors: S.Kishore Babu, Yarramreddy Abhinaya, Shaik Riyaz, Velamakuru Jhansi, Payardha Sharon Hephzibah

Abstract: In the contemporary digital landscape, establishing a compelling online presence has become an essential prerequisite for professional recognition and career advancement. Despite the proliferation of web development tools and portfolio platforms, the process of creating, personalizing, and deploying a professional portfolio website remains a technically demanding and time-consuming endeavor for many individuals. Craftly emerges as a transformative solution to this challenge — an AI-powered, full-stack web application that automates the end-to-end process of portfolio generation, customization, and live deployment using modern cloud infrastructure. Craftly integrates Google's Gemini AI API to intelligently parse uploaded resumes in PDF format, extracting structured professional data including personal details, skills, work experience, educational background, and project history. This parsed information is used to automatically pre-fill a portfolio editor, dramatically reducing manual data entry. Users may alternatively input their details manually, providing full flexibility in the content creation process. Once satisfied with their portfolio content, users select from nine professionally designed Handlebars-based HTML templates and deploy their portfolio to Amazon Web Services S3 as a static website — all within a single, unified interface. The deployment pipeline leverages Cloudflare Workers and Cloudflare DNS to provide each user with a unique, publicly accessible subdomain, enabling instant sharing of live portfolio URLs without requiring any domain management knowledge from the user. The backend infrastructure is containerized using Docker and deployed on AWS EC2, with Nginx serving as a reverse proxy for the Express.js API server. User authentication is handled via JSON Web Tokens (JWT), and all portfolio data is persisted in MongoDB. Preliminary evaluation of the system demonstrates significant reductions in the time required to create and publish a professional portfolio, with the end-to-end process from resume upload to live deployment achievable in under five minutes. Craftly represents a meaningful convergence of artificial intelligence, cloud computing, and user- centered design — democratizing professional web presence for students, job seekers, and professionals alike.

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Authors: Akshay Mahajan, Sahil Hashmi, Tannish Galhate, Anas Dange

Abstract: People's use of smartphones has increased rapidly in today's world, and as a result, a smartphone can be used effectively for personal security or various other protection purposes. On one hand, we get optimistic hope through a list of facts pertaining to woman empowerment, but on the other hand, we are chastised due to the crimes against women. Problems may come from anywhere and anytime, as women are also growing equally like men so for that purpose they have to travel alone at night where ever they go, they have to travel alone in public transport as well, and for that reason we need to understand and solve this problem of women so they also should not feel any fear regarding their safety. BESAFE aims at delivering a simple yet operational elucidation to this problem. BESAFE aims at developing a simple yet effective solution for empowering womanhood as well as installing a sense.

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Authors: Jn Chandra Sekhar, P Nagasri, V Nithinreddy, Sk Yaseen, S Praveen Kumar

Abstract: The rapid growth of digital education has exposed critical limitations in existing e- learning platforms, which predominantly rely on static, pre-built content repositories requiring substantial manual creation and maintenance effort. This paper presents EduVoxus, an AI- powered adaptive e-learning platform that integrates OpenAI's GPT-4o-mini model for dynamic content generation with ten machine learning algorithms implemented entirely from scratch, without reliance on external ML libraries such as scikit-learn, scipy, or numpy. The platform offers four distinct AI-driven learning modes: MCQ quizzes with adaptive difficulty, voice-based practice with speech recognition and AI evaluation, theory question generation and an AI chatbot for instant doubt resolution. The ten from-scratch ML algorithms span multiple domains of educational data mining: Exponential Weighted Moving Average (EWMA) for adaptive difficulty adjustment, SM-2 SuperMemo algorithm for spaced repetition flashcard scheduling, TF-IDF with cosine similarity for content-based recommendations, Ordinary Least Squares linear regression for score trend prediction, K- Means with K-Means++ initialization for learner clustering, user-based collaborative filtering with Pearson correlation, Bayesian Knowledge Tracing (BKT) for mastery estimation, Ebbinghaus forgetting curve modeling for optimal review scheduling, first- order Markov chains for study sequence prediction, and Gaussian Naive Bayes for at-risk learner classification. The platform additionally features comprehensive gamification (points, badges, streaks, leaderboards), role-based access control with user approval workflows, course management with study material uploads, community discussion forums with AI-assisted answers, SM-2 scheduled flashcard decks, bookmarkable Q&A, AI-generated study notes and automatic certificate generation. Built with Flask 3.1.3, SQLAlchemy, Bootstrap 5, Chart.js and Web Speech API, with PostgreSQL support for production deployment on Render.com. Comparative analysis demonstrates that EduVoxus offers capabilities not found in any single existing platform including BYJU'S, Coursera, Udemy and Khan Academy.

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Authors: ASR Reddy, S. Trisha, R. Venu Gopal, G. Sathvika, M. Venkatesh

 

Abstract: In this paper a new class of adjustable window function is proposed using a combination of Tangent hyperbolic function and Blackman-Harris 4-term window function. To derive the Tangent Hyperbolic Window function, the authors used the scaled independent variable Tangent hyperbolic functions shifted in opposite directions. The proposed window has the advantage of having 4-shape parameters that have lot of flexibility to vary the shape of the window for the desired spectral characteristics. The performance is compared with Hamming, Hanning, Kaiser and Gaussian windows in terms of the First Null Beam Width, Main Lobe Beam Width, Ripple ratio and Sidelobe roll-off ratio for the same window length with other windows presented for comparison. Simulation results show that Tanh window combined with Blackman-Harris window provides better sidelobe roll off characteristics and other spectral metrics that may be useful for some applications such as filter design and beamforming. Moreover, the paper presents the application of the proposed window in the field of array synthesis, and the comparison is performed with Hamming, Hanning, Kaiser and Gaussian windows. The results show that the array design with Tanh- Blackman-Harrish window provides better results in terms of the spectral metrics such as First Null Beam Width, Main Lobe Beam Width, Ripple ratio and Sidelobe roll-off ratio.

DOI: https://doi.org/10.5281/zenodo.19349175

 

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Authors: Md Tanvir Ahamed

Abstract: Software bugs remain one of the most persistent challenges in software development, consuming 50-75% of developer time and costing the global economy over $2 trillion annually. This paper presents a multi-language approach to automated bug detection and fixing using the T5-Small transformer model. We construct a dataset of 2,600 real bug examples from Defects4J, BugSwarm, QuixBugs, GitBugs, and 500 novel multi-error examples. The T5-Small model (60M parameters) is fine-tuned with optimal hyperparameters. Our evaluation framework employs seven metrics with mathematical formulations. Experimental results demonstrate 68.46% Normalized Exact Match, 93.74% F1 Score, and 99.55% ROUGE-1. The model performs effectively on both Python (70.0%) and Java (65.0%). All artifacts are released open-source.

DOI: https://doi.org/10.5281/zenodo.19970345

Published by: vikaspatanker

Authors: Rajani Devi K, Gowri Sankar R, Gayathri Reddy R, Harsha Vardhan V, Srikanth T

Abstract: In the modern software development landscape, countless developers—particularly students, beginners, and hobbyists—build innovative web applications but fail to deploy them to the internet due to the complexity of traditional deployment processes. Deploying an application requires extensive knowledge of cloud platforms such as AWS, GCP, or Cloudflare, involving technical hurdles including renting and configuring cloud instances, purchasing domains, setting up web servers, and managing infrastructure. This steep learning curve creates a significant barrier to entry, causing many developers to abandon their fully-functional applications at the development stage without ever making them publicly accessible, thereby limiting innovation visibility and preventing developers from building their portfolios.

 

 

Published by: vikaspatanker