An empiric path towards fraud detection and protection for NFC-enabled mobile payment system

The synthesis of NFC technology accompanying mobile payment is a state-of-the-art resolution for payment users. In view of rapid development in electronic payment system there is rise in fraudulent activity in banking transactions associated with credit cards and card-not-present transaction. M-Commerce aid the consumers and helps to bestow real-time information in payment system. Due to the familiarization of m-commerce there is cogent increase in the number of fraudulent activities, emerging in billions of dollar loss every year worldwide. To absolute the security breaches, payment transactions could be confined by considering various parameters like user and device authentication, consumer behavior pattern, geolocation and velocity. In this paper we formally assay NFC-enabled mobile payment fraud detection ecosystem using score-based evaluation method. The fraud detection ecosystem will provide a solution based on transaction risk-modeling, scoring transaction, business rule-based, and cross-field referencing. The score-based evaluation method will analyze the transaction and reckon every transaction for fraud risk and take pertinent decision

An empiric path towards fraud detection and protection for NFC-enabled mobile payment system

The synthesis of NFC technology accompanying mobile payment is a state-of-the-art resolution for payment users. In view of rapid development in electronic payment system there is rise in fraudulent activity in banking transactions associated with credit cards and card-not-present transaction. M-Commerce aid the consumers and helps to bestow real-time information in payment system. Due to the familiarization of m-commerce there is cogent increase in the number of fraudulent activities, emerging in billions of dollar loss every year worldwide. To absolute the security breaches, payment transactions could be confined by considering various parameters like user and device authentication, consumer behavior pattern, geolocation and velocity. In this paper we formally assay NFC-enabled mobile payment fraud detection ecosystem using score-based evaluation method. The fraud detection ecosystem will provide a solution based on transaction risk-modeling, scoring transaction, business rule-based, and cross-field referencing. The score-based evaluation method will analyze the transaction and reckon every transaction for fraud risk and take pertinent decision. Copyright © 2019 Universitas Ahmad Dahlan. All rights reserved

Opinion mining using combinational approach for different domains

An increase in use of web produces large content of information about products. Online reviews are used to make decision by peoples. Opinion mining is vast research area in which different types of reviews are analyzed. Several issues are existing in this area. Domain adaptation is emerging issue in opinion mining. Labling of data for every domain is time consuming and costly task. Hence the need arises for model that train one domain and applied it on other domain reducing cost aswell as time. This is called domain adaptation which is addressed in this paper. Using maximum entropy and clustering technique source domains data is trained. Trained data from source domain is applied on target data to labeling purpose A result shows moderate accuracy for 5 fold cross validation and combination of source domains for Blitzer et al (2007) multi domain product dataset

The Fact-Finding Security Examination in NFC-enabled Mobile Payment System

Contactless payments devised for NFC technology are gaining popularity. Howbeit, with NFC technology permeating concerns about arising security threats and risks to lessen mobile payments is vital. The security analysis of NFC-enabled mobile payment system is precariously imperative due to its widespread ratification. In mobile payments security is a prevalent concern by virtue of the financial value at stave. This paper assays the security of NFC based mobile payment system. It discusses the security requirements, threats and attacks that could occur in mobile payment system and the countermeasures to be taken to secure pursuance suitability

Nexus between foreign exchange rate and stock market: evidence from India

This study examines the impact of foreign exchange rate fluctuations on various NSE capitalized indices of India. Five exchange rates were chosen based on trading contracts in the currency derivative segment of NSE. These exchange rates are US Dollar-Indian Rupee (USD/INR), Euro-Indian Rupee (EUR/INR), Great Britain Pound-Indian Rupee (GBP/INR), Chinese Yuan-Indian Rupee (CNY/INR) and Japanese Yen-Indian Rupee (JPY/INR), which are used as a regressor in this study. The data of NSE Nifty large-cap 100, Nifty mid-cap 100 and Nifty small-cap from December 1, 2012 to December 1, 2022 was considered for the study. GARCH (1, 1) model was used to analyze the nexus between exchange rate fluctuations and capitalized indices, and it was further validated by DCC GARCH to evaluate the volatility spillover. The result shows that exchange rate fluctuations have a positive effect on stock market volatility along with a varying degree of incidence on small-cap, mid-cap, and large-cap. DCC α has been found to be significant in USD & GBP for small-cap, and GBP & CNY for mid-cap. On the other hand, USD, Euro, CNY and JPY have a significant impact on the large-cap index in the short-run. Further, it is found that there is long-run spillover effect (DCC β) of exchange rates on all capitalized indices of the Indian stock market, and it is highest in in the large-cap case

Genomic characterization of Plasmodium falciparum genes associated with anti-folate drug resistance and treatment outcomes in eastern India: A molecular surveillance study from 2008 to 2017

IntroductionAfter being used vigorously for the previous two decades to treat P. falciparum, chloroquine and sulfadoxine-pyrimethamine were replaced in 2009 with an artemisinin-based combination therapy (artesunate-sulfadoxine-pyrimethamine) in an effort to combat multidrug-resistant parasites.MethodsWe set out to assess the genetic variants of sulfadoxine-pyrimethamine resistance and the effectiveness of its treatment in eastern India prior to, during, and 6 to 8 years following the introduction of the new pharmacological regime. In 2008-2009, 318 P. falciparum–positive patients got the recommended doses of sulfadoxine-pyrimethamine. We used 379 additional isolates from 2015 to 2017 in addition to the 106 isolates from 2010. All 803 isolates from two study sites underwent in vitro sulfadoxine-pyrimethamine sensitivity testing and genomic characterisation of sulfadoxine-pyrimethamine resistance (pfdhfr and pfdhps).ResultsIn Kolkata and Purulia, we observed early treatment failure in 30.7 and 14.4% of patients, respectively, whereas recrudescence was found in 8.1 and 13.4% of patients, respectively, in 2008–2009. In 2017, the proportion of in vitro pyrimethamine and sulfadoxine resistance steadily grew in Kolkata and Purulia despite a single use of sulfadoxine-pyrimethamine. Treatment failures with sulfadoxine-pyrimethamine were linked to quintuple or quadruple pfdhfr- pfdhps mutations (AICII-AGKAT, AICII-AGKAA, AICII-SGKGT, AICII-AGKAA, AICNI-AGKAA) in 2008–2009 (p < 0.001). The subsequent spread of mutant-haplotypes with higher in vitro sulfadoxine-pyrimethamine resistance (p < 0.001), such as the sextuple (dhfr-AIRNI+dhps-AGEAA, dhfr-ANRNL+dhps-AGEAA) and septuple (dhfr-AIRNI+dhps-AGEAT), mutations were observed in 2015-2017.DiscussionThis successive spread of mutations with high in vitro sulfadoxine-pyrimethamine resistance confirmed the progressive increase in antifolate resistance even after an 8-year withdrawal of sulfadoxine-pyrimethamine

Entropy based classifier for cross-domain opinion mining

In recent years, the growth of social network has increased the interest of people in analyzing reviews and opinions for products before they buy them. Consequently, this has given rise to the domain adaptation as a prominent area of research in sentiment analysis. A classifier trained from one domain often gives poor results on data from another domain. Expression of sentiment is different in every domain. The labeling cost of each domain separately is very high as well as time consuming. Therefore, this study has proposed an approach that extracts and classifies opinion words from one domain called source domain and predicts opinion words of another domain called target domain using a semi-supervised approach, which combines modified maximum entropy and bipartite graph clustering. A comparison of opinion classification on reviews on four different product domains is presented. The results demonstrate that the proposed method performs relatively well in comparison to the other methods. Comparison of SentiWordNet of domain-specific and domain-independent words reveals that on an average 72.6% and 88.4% words, respectively, are correctly classified

Social inputs analysis targeting an individual and group

Presence of discernment is astonishingly of paramount importance. Decision-making is highly influenced by a variety of factors. These factors convey distinct types of information to the decision-maker. The proposed system aims at understanding the influence of personality preferences and a group on an individual. Myers-Briggs Type Indicator measures the personality preferences on four specific dimensions and has been used by psychologists on many occasions since ages. This study uses MBTI preferences as a reference, to explore their impacts on an individual. The second important factor analyzed in this article includes the influence of peer pressure. The target audience for this study is youths, as this exploration would help the students understand the influence of external factors on their decision-making power. This system aims at abridging the gap in achieving their career goals and hence deducing what the student might be interested in irrespective of what his/her friend’s preferences are