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Full-Text Articles in Other Computer Engineering
Device Free Indoor Localization Of Human Target Using Wifi Fingerprinting, Prasanga Neupane
Device Free Indoor Localization Of Human Target Using Wifi Fingerprinting, Prasanga Neupane
LSU Master's Theses
Indoor localization of human objects has many important applications nowadays. Proposed here is a new device free approach where all the transceiver devices are fixed in an indoor environment so that the human target doesn't need to carry any transceiver device with them. This work proposes radio-frequency fingerprinting for the localization of human targets which makes this even more convenient as radio-frequency wireless signals can be easily acquired using an existing wireless network in an indoor environment. This work explores different avenues for optimal and effective placement of transmitter devices for better localization. In this work, an experimental environment is …
Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami
Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami
Future Computing and Informatics Journal
This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …
Iot Malicious Traffic Classification Using Machine Learning, Michael Austin
Iot Malicious Traffic Classification Using Machine Learning, Michael Austin
Graduate Theses, Dissertations, and Problem Reports
Although desktops and laptops have historically composed the bulk of botnet nodes, Internet of Things (IoT) devices have become more recent targets. Lightbulbs, outdoor cameras, watches, and many other small items are connected to WiFi and each other; and few have well-developed security or hardening. Research on botnets typically leverages honeypots, PCAPs, and network traffic analysis tools to develop detection models. The research questions addressed in this Problem Report are: (1) What machine learning algorithm performs the best in a binary classification task for a representative dataset of malicious and benign IoT traffic; and (2) What features have the most …