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Research Paper

OpenXploit: An Automated Approach to Vulnerability Assessment and Penetration Testing

Vulnerability assessment (VA) and penetration testing (Pen-Test) are required for security auditing and compliance. Converting VA scan results to be usable in Pen-Test tools is difficult because it must be done at various stages using software tools. This paper describes a system that automatically converts Open Vulnerability Assessment Scanner results into exploitable scripts for Metasploit, an open-source pen-testing program. It targets the top ten vulnerabilities identified by the Open Web Application Security Project and tests them with Metasploit. The system consists of three major components: Scan Result Extraction, which extracts VA scan results related to OWASP 10 vulnerabilities; Target List Repository, which stores vulnerability lists for Metasploit; and Automated Shell Scripts Exploitation, which generates scripts to render the exploit module for execution in Metasploit. The prototype was tested with a variety of scenarios, converting scan results to shell code and rendering them in Metasploit. The experimental results confirmed that the system was functionally correct across all test cases.

Published by: Manav Agarwal, Shrushti Patil, Dr. Suvarna Patil, Mrs. Sneha Kanawade

Author: Manav Agarwal

Paper ID: V11I3-1303

Paper Status: published

Published: June 6, 2025

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Research Paper

Vision Assist System Using Deep Learning For Product And Text Recognition For Blind People

For blind persons it is very essential to recognize a product of their daily use so we implied a method to identify product in their everyday routine by use of camera. To separate an object from un-necessary background, movement-based technique is used to spot object of concern from the camera by instructing person about recognized objects. The goal of the present project is to model an object detector to detect objects for visually impaired people and other commercial purposes by recognizing the objects at a particular distance. Available old techniques for object detection needed large training data it takes more time and it’s quite complicated and it’s a difficult task. Object detection is used in many scenarios. Conventional methods of these object detection depend on huge number of datasets and it also takes large amount of time to train these data. Training of small or unseen objects is a more challenging task. Human brains and visual systems are more accurate and faster in detecting objects in real time and has conscious thoughts in detecting obstacles. Due to the availability of large amount of data and with more advanced technologies and better working algorithms, classification and detection of multiple objects in the same frame has become easy with high accuracy. The main objective of the project is to design and implement a real time object recognition using real time camera with navigation system. And also using implement text detection and recognition system to extract the text from captured image using Optical character recognition algorithm. We can implement the system in real time environment using Python as front end.

Published by: Vijaya Lakshmi S, Madhu Varshini B, Kokila R

Author: Vijaya Lakshmi S

Paper ID: V11I3-1304

Paper Status: published

Published: June 6, 2025

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Research Paper

Re-Imagining Emergency Response System with Geo Fencing

Despite the existence of emergency hotlines, many distress calls go unanswered, leaving individuals in urgent need without timely assistance. This study proposes a system designed to enhance the speed and reliability of Emergency Response Services(ERS). By integrating advanced technologies such as signal triangulation, Geo-fencing, Geo-location, predictive AI, and Geo data analytics, the system aims to provide more accurate and faster responses. The approach works within India’s current governance framework and collaborates with community networks to improve safety, particularly for vulnerable groups like women and children. The proposed system’s objectives include reducing the response time for emergency services, ensuring that help reaches those in need quickly, and strengthening overall crisis management. By leveraging predictive AI and Geo data, it optimizes response times. This study presents an innovative solution for improving emergency services, making them more inclusive, effective, and contributing to the overall safety of communities.

Published by: Aryav Goyal, Isha Goel

Author: Aryav Goyal

Paper ID: V11I3-1290

Paper Status: published

Published: June 5, 2025

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Research Paper

Cyber Warfare: Conflicts and Role of Security in the Digital Age

This research paper looks at a brand new evolving form of warfare, “ cyber warfare”.The main focus is primarily on the internal and external notions of security and emphasises how cybersecurity affects both. Various examples have been taken up to demonstrate how cyber terrorism has created havoc all over the world. An in-depth analysis of the development of international laws was conducted.

Published by: Vanshika Rao

Author: Vanshika Rao

Paper ID: V11I3-1288

Paper Status: published

Published: June 3, 2025

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Research Paper

Divided by Wealth: A Deep Dive into Women’s Access to Credit

Women’s access to credit has historically been restricted by systemic discrimination and by outdated financial structures, limiting female economic independence and business opportunities. While landmark pieces of legislation such as the 1974 Equal Credit Opportunity Act (ECOA) in the United States have attempted to address these issues, research continues to indicate that gender biases in credit persist. While previous academic studies have examined econometrics, Fletschner (2008), and legal reforms, Garikipati (2008), this paper argues that deeply ingrained societal biases continue to shape credit lending systems, disproportionately disadvantaging women. By analyzing case studies from the United States, India, and South Korea, this research evaluates how gender-based disparities in credit access manifest across different economic and cultural contexts. The study incorporates data from financial institutions, government reports, and scholarly articles to highlight ongoing barriers. Ultimately, this paper argues that while progress has been made, financial institutions remain skewed in favor of men, necessitating policy changes that prioritize inclusivity and fairness. Without reform, women will continue to face unnecessary hurdles in obtaining credit, reinforcing long-standing economic inequalities.

Published by: Krish Gupta

Author: Krish Gupta

Paper ID: V11I3-1282

Paper Status: published

Published: June 3, 2025

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Research Paper

AI-Driven Medical Fundraising Verification System to Detect and Prevent Fraudulent Treatment Requests

Medical fund fraud, where individuals fake treatment documents to solicit donations, is a growing concern in crowdfunding. Traditional verification methods are often manual, slow, and prone to error. This project introduces an AI-based system using YOLOv8 to detect text in medical bills and Paddle OCR to extract key information. Extracted data—like hospital names and treatment costs—is verified using fuzzy matching against a trusted hospital database. This automated approach enhances accuracy, blocks fraudulent requests, and helps restore donor trust.

Published by: D V Vidhya Sri, N Aravindhan

Author: D V Vidhya Sri

Paper ID: V11I3-1280

Paper Status: published

Published: June 1, 2025

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