No abstract

No abstract

No abstract

No abstract

In this digital era, a huge amount of money had been laundered via digital frauds, which mainly occur in the timeframe of electronic payment transaction made by first-time credit/debit card users. Currently, Finance organizations are facing several fraud attempts and it likely happens due to the current infrastructure, which only has an older database.. The current infrastructure diminishes the working environment of any finance organization sector with frequent fraud attempts. In this perspective, the roposed research article provides an overview for the development of an automated prevention system for any finance organization to protect it from any fraudulent attacks. The proposed automated case management system is used to monitor the expenses of the behavior study of users by avoiding the undesirable contact. The proposed research work develops a new management procedure to prevent the occurrence of electronic fraud in any finance organization. The existing procedure can predict digital fraud with an old updated database. This creates disaster and destructive analysis of the finance segment in their procedure. The cyber fraud phenomenon prediction is used to predict the fraud attempt with content-based analysis. The lack of resources is one of the enormous challenges in the digital fraud identification domain. The proposed scheme addresses to integrate all safety techniques to safeguard the stakeholders and finance institutions from cyber-attacks.

While the phrase Big Data analytics is not only applicable for a certain realm of technology, diverse business segments like banking also benefit from the use of advanced mathematical and statistical models like predictive analysis, artificial intelligence, and data mining. If it is a query that is data volume generated in a bank or any financial institution is huge, it is absolutely a yes. As per the recent survey, it is observed that banks worldwide aren't just concentrating on improving the asset quality and fulfilling regulatory compliance but on the lookout for a digital convergence strategy to reach customers effectively in delivering services and products. As most of the data generated in internet banking and ATM transactions are unstructured accounting around for 2.5 quintillion bytes useful for fraud detection, risk management, and customer satisfaction, the use of trending Big Data Analytics methodology can be used to tackle the challenges and competition among banks. There are surplus advantages of Big Data strategy in the banking field and in this paper, we have made an analysis over Big Data Analytics on banking applications and their related concepts.

The internet connectivity extended by the internet of things to all the tangible things lying around and used by us in our day today life has convert the devices into smart objects and led to huge set of data generation that holds both the valuable and invaluable information. In order to perfectly handle the information’s generated and mine the valuables from them, the analytics are engaged by the cloud. To have a timely access, most probably the fog services are preferred than the cloud as they bring down the service of the cloud to the user edge and reduces the time complexity in accessing of the information. So the paper proposes the big data analytics for the fog assisted health care application to effectively handle the health information’s diagnosed for the aged persons. The proposed model is simulated using the IFogSim toolkit to examine the performance fogassisted smart healthcare application.

The routing in the wireless sensor networks has significant part in enhancing the functioning of the network as the improper routing methodologies and the routing deteriorates the energy of the sensor networks, affecting the lifespan of the network, leading to link failures and the connectivity problems. The necessity to improve the network performance is the main focus of the paper, so the paper presents the performance analysis of the evolutionary algorithms such as Genetic Algorithm, Ant lion optimization, Particle swarm optimization and Ant colony optimization and evaluates the routes obtained using the fuzzy Petri Net model, to find out the optimal route for the wireless sensor networks. The simulation through the python in terms of the some resource validates the optimal path in terms of energy, network life time and the packet delivery ratio.