| No. |
Title and Author |
Area |
Country |
Page |
| 1 |
A Cryptographic System Based on Blockchain and Attributes For Sharing Medical Data
-Pavithra S
Medical information contains a great deal of personal data and is quite sensitive to privacy concerns. Given the increasing volume of information in the healthcare sector, medical data must be appropriately and safely kept in this big data era. However, sharing current medical information can be risky and challenging because of the potential for privacy violations. To solve these issues, this study proposes a blockchain framework-based storage solution for healthcare information security along with attribute-based access control. The concept uses attribute-based access management to enable dynamic and granular access to medical data, which can be made secure and impenetrable before being stored in the blockchain system by creating related crypto contracts. Moreover, IPFS technology is incorporated into this solution to ease the blockchain's storage burden. Experiments demonstrate that the suggested system in this study, which combines Demonstrations reveal that the scheme proposed in this paperwork on the combination of access control of attributes and blockchain technology will not only takes care of the storage and uprightness of medical data but also have more productivity while accessing the medical information. Read More...
|
Engineering |
India |
1-9 |
| 2 |
Vehicle Damage Detection Using Deep Learning With Yolo Algorithm
-Dhrupad Thanvi ; Soham Loke; Hitesh Bhanushali; Yash Musale
1) Data Preparation: Data Quality Having good quality annotated photographs is essential. Include a variety of car models, perspectives, and damage types (scratches, dents, broken parts, etc.). 2) Diversity: The dataset should represent a variety of backdrops, climates, and lighting conditions in order to improve model generalization. Tools for Annotation: Applications such as LabelImg, Roboflow, or CVAT can be used to expedite the annotation process. Class Imbalance: Address class imbalance (e.g., more minor scratches vs fewer damaged components) to prevent bias in forecasts. 3) YOLO versions 7 and 8 Features: YOLOv7: Very quick and accurate. emphasizes extremely precise real-time detection, which qualifies it for applications such as insurance and on-site inspection. YOLOv8: More user-friendly and with improved inference and training support. improved model. Read More...
|
Information Technology |
India |
10-13 |
| 3 |
Nanomaterial-Based Biosensors: From Theoretical Modelling to Practical Applications
-Keshav Kumar ; Er Veena Rani
Nanomaterial-based biosensors have emerged as a revolutionary approach to detecting biological and chemical analytes, offering unparalleled sensitivity, selectivity, and versatility. This study explores the integration of advanced nanomaterials, such as graphene, carbon nanotubes, and metal nanoparticles, into biosensor technologies. Employing theoretical modeling techniques, including Density Functional Theory (DFT), the research elucidates the interaction mechanisms between nanomaterials and target analytes, providing critical insights into adsorption energy, charge transfer, and electronic structure modifications. The experimental phase synthesizes and characterizes nanomaterials, focusing on optimizing their structural, chemical, and electronic properties for biosensing applications. These materials are incorporated into electrochemical, optical, and field-effect transistor (FET) sensor platforms, demonstrating enhanced performance metrics, including ultra-low detection limits, rapid response times, and exceptional specificity. Applications span healthcare diagnostics, environmental monitoring, and food safety, addressing pressing global challenges such as disease detection, pollutant monitoring, and quality control. The study highlights the scalability and reproducibility of nanomaterial-based biosensors and discusses integration with emerging technologies like artificial intelligence for real-time data analysis. This work establishes a comprehensive framework for designing next-generation biosensors, leveraging the unique properties of nanomaterials to achieve breakthroughs in sensitivity, miniaturization, and multifunctionality. Read More...
|
Electronics & Communication Engineering |
India |
14-18 |
| 4 |
Fraudulent Login Detection Using AI
-Harshitha H B ; Abhineeth Aalthoor; B R Yashaswini; C Smriti Emmanuel; Kushal Mandivya
With the rapid evolution of digital technology, securing user accounts has become an increasingly crucial challenge. Traditional authentication mechanisms, including passwords and static rule-based security protocols, have become vulnerable to cyber threats such as credential stuffing, phishing, and brute-force attacks. This paper presents an AI-powered system to enhance login security by analyzing user behavior and detecting anomalous activities indicative of fraudulent logins. By employing a machine learning-based approach, the system evaluates key factors such as IP address, geographical location, login frequency, and device fingerprinting to detect unauthorized access attempts. The model dynamically adapts to new threats by continuously learning from historical login patterns. The proposed solution enhances cybersecurity while maintaining a seamless user experience by minimizing false positives. Read More...
|
Computer Science & Engineering |
India |
19-20 |
