{"id":8448,"date":"2020-07-15T12:39:12","date_gmt":"2020-07-15T07:09:12","guid":{"rendered":"https:\/\/codeshoppy.com\/shop\/?post_type=product&p=8448"},"modified":"2022-09-27T17:21:54","modified_gmt":"2022-09-27T11:51:54","slug":"credit-card-fraud-detection-system","status":"publish","type":"product","link":"https:\/\/codeshoppy.com\/shop\/product\/credit-card-fraud-detection-system\/","title":{"rendered":"Credit Card Fraud Detection System Dotnet"},"content":{"rendered":"

Credit Card Fraud Detection System using asp.net with Csharp<\/h2>\n

The credit card fraud detection features uses user behavior and location scanning to check for unusual patterns. These patterns include user characteristics such as user spending patterns as well as usual user geographic locations to verify his identity.<\/p>\n

\u00a0If any unusual pattern is detected, the system requires revivification.
\nCredit Card Fraud Detection System<\/strong> <\/em><\/a>The system analyses user credit card data for various characteristics. These characteristics include user country, usual spending procedures. Based upon previous data of that user the system recognizes unusual patterns in the payment procedure. So now the system may require the user to login again or even block the user for more than 3 invalid attempts.A FDS keeps running at a charge card issuing bank. Every approaching exchange is submitted to the FDS for check. FDS gets the card points of interest and the estimation of procurement to confirm, regardless of whether the exchange is bona fide or not. The sorts of products that are purchased in that exchange are not known to the FDS. It tries to discover any inconsistency in the exchange in view of the spending profile of the cardholder, shipping location, and charging address, and so on.<\/p>\n

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Credit Card Fraud Detection System<\/a><\/h3>\n
<\/i> 1 file(s) <\/i> 15.71 KB<\/div>\n <\/div>\n
\n Download<\/a>\n <\/div>\n <\/div>\n <\/div>\n<\/div>\n\n<\/div>\n

Credit Card Fraud Detection System<\/h2>\n

Existing System<\/strong><\/h2>\n

If there should be an occurrence of the current framework the extortion is recognized after the misrepresentation is done that is, the misrepresentation is distinguished after the dissension of the card holder. Thus the card holder confronted a considerable measure of inconvenience before the examination wrap up. And furthermore as all the exchange is kept up in a log, we have to keep up gigantic information.<\/p>\n

DISADVANTAGES<\/strong><\/p>\n

Online buy is made so we don\u2019t have a clue about the individual how is utilizing the card on the web, we simply catch the IP address for confirmation reason. So there require an assistance from the cybercrime to examine the misrepresentation. To dodge the whole above disservice we propose the framework to recognize the misrepresentation in a best and simple way.<\/p>\n

Proposed System<\/strong><\/h2>\n

In proposed framework, to introduce a Hidden Markov Model (HMM).Which does not require extortion marks but then can recognize cheats by considering a cardholder\u2019s way of managing money. Card exchange handling grouping by the stochastic procedure of a HMM.<\/p>\n

The points of interest of things acquired in Individual exchanges are normally not known to a FDS running at the bank that issues charge cards to the cardholders. Consequently, we feel that HMM is a perfect decision for tending to this issue. Another vital preferred standpoint of the HMM-based approach is an uncommon decrease in the quantity of False Positives exchanges distinguished as vindictive by a FDS in spite of the fact that they are really certified.<\/p>\n

Advantages<\/strong><\/p>\n

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  1. The identification of the extortion utilization of the card is discovered substantially speedier that the current framework.<\/li>\n
  2. If there should arise an occurrence of the current framework even the first card holder is additionally checked for misrepresentation discovery. Yet, in this framework no compelling reason to check the first client as we keep up a log.<\/li>\n
  3. The log which is kept up will likewise be a proof for the bank for the exchange made.<\/li>\n
  4. We can locate the most precise discovery utilizing this procedure.<\/li>\n
  5. This diminish the dreary work of a representative in the bank<\/li>\n<\/ol>\n

    HARDWARE REQUIREMENTS <\/strong><\/h2>\n

    System\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0 :\u00a0 Intel3core<\/p>\n

    HardDisk \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 :\u00a0 8GB<\/p>\n

    Monitor \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 :\u00a0 14\u2019ColorMonitor<\/p>\n

    Mouse\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 :\u00a0\u00a0 Optical Mouse<\/p>\n

    SOFTWARE REQUIREMENTS<\/strong><\/h2>\n

    Operating system\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 :\u00a0 Windows7\/8\/10<\/p>\n

    Coding Language\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 :\u00a0\u00a0 ASP.Net with C# (Service Pack 1)<\/p>\n

    Data Base\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 :\u00a0\u00a0 SQL Server 2014<\/p>\n

    Tools\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 :\u00a0 Visual studio 2013<\/p>\n

    <\/h2>\n

    Functionality Performed by Admin and User:<\/strong><\/p>\n

    These are the functionality performed by Admin and User<\/p>\n

    Modules <\/strong><\/h2>\n

    This Project has following Modules:<\/p>\n

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    • Admin<\/strong><\/li>\n
    • User<\/strong><\/li>\n<\/ul>\n

      1) Admin Module<\/strong><\/p>\n

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      • Home<\/li>\n
      • View User<\/li>\n
      • View Blocked User<\/li>\n
      • View All Transaction<\/li>\n
      • Logout<\/li>\n<\/ul>\n

        2) User Module<\/strong><\/p>\n

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        • Home<\/li>\n
        • Transaction<\/li>\n
        • Product<\/li>\n
        • View Profile<\/li>\n
        • View Log<\/li>\n
        • Logout<\/li>\n<\/ul>\n

          \n","protected":false},"excerpt":{"rendered":"

          Credit Card Fraud Detection System using asp.net with Csharp The credit card fraud detection features uses user behavior and location<\/p>\n","protected":false},"featured_media":8457,"template":"","meta":{"_joinchat":[]},"product_brand":[],"product_cat":[22],"product_tag":[],"class_list":{"0":"post-8448","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-dotnetcsharp","8":"first","9":"outofstock","10":"shipping-taxable","11":"purchasable","12":"product-type-simple"},"_links":{"self":[{"href":"https:\/\/codeshoppy.com\/shop\/wp-json\/wp\/v2\/product\/8448","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/codeshoppy.com\/shop\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/codeshoppy.com\/shop\/wp-json\/wp\/v2\/types\/product"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/codeshoppy.com\/shop\/wp-json\/wp\/v2\/media\/8457"}],"wp:attachment":[{"href":"https:\/\/codeshoppy.com\/shop\/wp-json\/wp\/v2\/media?parent=8448"}],"wp:term":[{"taxonomy":"product_brand","embeddable":true,"href":"https:\/\/codeshoppy.com\/shop\/wp-json\/wp\/v2\/product_brand?post=8448"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/codeshoppy.com\/shop\/wp-json\/wp\/v2\/product_cat?post=8448"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/codeshoppy.com\/shop\/wp-json\/wp\/v2\/product_tag?post=8448"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}