A Model Based on Convolutional Neural Network for Online Transaction Fraud Detection

<div>Different <svg height="11.5695pt" id="M82" style="vertical-align:-3.18152pt" version="1.1" viewbox="-0.0498162 -8.38798 11.9489 11.5695" width="11.9489pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M493 503C489 551 484 614 483 650H43V622C120 616 128 611 128 525V126C128 40 120 34 40 28V0H312V28C221 34 213 40 213 126V307H316C407 307 412 296 424 227H453V420H424C412 355 407 346 316 346H213V584C213 613 216 616 246 616H322C398 616 419 607 436 579C449 559 455 539 464 499L493 503Z" id="g121-68"></path></g><g transform="matrix(.0091,0,0,-0.0091,6.877,3.132)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z" id="g50-50"></path></g></svg> scores of the three models on various sample sets.</div>

Security and Communication Networks

fig11

Figure 11

Figure 11: A Model Based on Convolutional Neural Network for Online Transaction Fraud Detection 