Due to the rise and rapid growth of E-Commerce, use of credit cards for online purchases has dramatically increased and it caused an explosion in the credit card fraud. As credit card becomes the most popular mode of payment for both online as well as regular purchase, cases of fraud associated with it are also rising. In real life, fraudulent transactions are scattered with genuine transactions and simple pattern matching techniques are not often sufficient to detect those frauds accurately. Implementation of efficient fraud detection systems has thus become imperative for all credit card issuing banks to minimize their losses. Many modern techniques based on Artificial Intelligence, Data mining, Fuzzy logic, Machine learning, Sequence Alignment, Genetic Programming etc., has evolved in detecting various credit card fraudulent transactions. A clear understanding on all these approaches will certainly lead to an efficient credit card fraud detection system. This paper presents a survey of various techniques used in credit card fraud detection mechanisms and evaluates each methodology based on certain design criteria.
In current wireless systems, the claim for rapid data services has become unavoidable in broadband communication. Single carrier frequency division multiple access (SC‐FDMA) has remained a multiple access (MA) technique with low peak‐to‐average power ratio (PAPR) in 4G systems. Non‐orthogonal multiple access (NOMA) is a complimentary MA technique in the fifth generation (5G) new radio with the capability of using similar frequency elements for multiuser communication within a single cellular system. In SC‐FDMA NOMA systems the carrier frequency offsets (CFO) destroy the orthogonal behavior in multiple carriers during transmission leading to inter‐carrier interference (ICI) and multiple access interference (MAI). Furthermore, the power allocated for each user in the NOMA cluster exhibits a noticeable part in enhancing the performance of the system. In this article, we propose a joint low‐complexity linear regularized zero forcing (JLC‐LRZF) for SC‐FDMA NOMA system and investigate its performance using discrete Fourier transform (DFT) and discrete cosine transform (DCT). The proposed JLC‐LRZF equalization algorithm is capable of performing equalization and CFO compensation with low‐complexity with banded‐matrix approximation (BMA). Additionally, we investigate the effectiveness of SC‐FDMA NOMA system in achieving improved performance with different values of CFO and power allocation policies in uniform random multipath channels.
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