BibTeX:

@article{IJIRSTV4I5007,
     title={Analysis of Fraudulent in Graph Database for Identification and Prevention},
     author={Deepak Singh Rawat, Rajesh Shyam Singh and Dr. H. L. Mandoria},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={4},
     number={5},
     pages={42--49},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV4I5007.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

The world is changing, and this is the digital era. Almost everything around us is digitized and the flow of information is huge from a variety of sources ranging from mobile phone, smart devices, surveillance, sensors of the universe, weather forecasting sensors, medical equipment, customers transactions of the internet, user behaviours on the internet, and so on. Billions of dollars get wasted every year due to fraud. Traditional methods of fraud detection play an important role in minimizing these losses. Increasingly fraudsters have developed a variety of way to elude their detection, both by working together and by leveraging various other means of constructing fake identities. This paper proposed a new approach for fraud prevention in different sector with help of graph database by identifying of previous fraud records in graph database.

Graph Database, Graph DB, Graph Dataset, Frauds, online Frauds