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All Journal International Journal of Public Health Science (IJPHS) Indonesian Journal of Electrical Engineering and Computer Science
Shaik Mazhar Hussain
Middle East College
Health Professions

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Design and development for detection and prevention of ATM skimming frauds Sultan Saleem Khalaf Al Hattali; Shaik Mazhar Hussain; Anilloy Frank
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 3: March 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i3.pp1224-1231

Abstract

ATM Skimming is a major concern that needs to be addressed with a specific solution. ATM Skimming is done in two steps. One is stealing the Personal Information that is stored on the Debit card / Credit card using Rain cover connected to the card reader slot (ATM’s real card slot). The second is installing a Fake keypad that can capture the pin code when the card holder enters pin details. Few researchers have proposed solutions to address the issue using Image Processing techniques. However, it does not provide a complete solution in a long term. Hence it is of paramount importance to provide ATM with high security features. In order to solve the issue of ATM Skimming, An Embedded System design is proposed. The research is carried out in two phases. One is detection phase and the second is Prevention Phase. In the detection phase, Hardware components such as Arduino Mega, Force Sensing Resistor (FSR), GPS, GSM and Buzzer are used. Arduino Mega acts as a Central Processor that processes the information received from Force sensing resistor (FSR) and send SMS Messages to ROP and Bank Officials using GSM and informing them about the ATM Location using GPS where the Fraud is taking place. Buzzer can be used at the ATM Locations to alert nearby people. In the prevention Phase, as a preventive measure a Onetime password (OTP) technique is used. If a fraudster somehow succeeds in Fixing fake key pad and Rain Cover at ATM’s real card slot, When he tries to insert debit card, An OTP will be generated and is sent to the Card Holder which in turn he can know someone is trying to make Transactions and quickly he can ask bank officials to Block his account and inform ROP about the same. Expected findings of the proposed work is to detect  Fake keypads and Fake card readers using FSR placed at the edges of Original Keypad and card reader slot. Sending messages to ROP, BANK OFFICIALS and CARD HOLDER using GSM. ATM locations are identified using GPS. Buzzers are used to alert nearby people.
Detection and prediction of monkey pox disease by enhanced convolutional neural network approach Shaik Mazhar Hussain; Syed Ghouse
International Journal of Public Health Science (IJPHS) Vol 12, No 2: June 2023
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v12i2.22310

Abstract

Monkeypox is an infectious viral disease affecting both humans and animals. All symptoms are accompanied by a fever, swollen lymph nodes, and a rash that blisters before crusting. The interval between exposure and the development of symptoms is 5 to 21 days. Typically, symptoms last between two and four weeks. Although it is unknown to what degree it can happen without any signs. It has been found that not all outbreaks display the typical symptoms of fever, aches in the muscles, enlarged glands, and lesions appearing simultaneously. Cases may be severe, especially in children, pregnant women, or people with compromised immune systems. The problem can be detected and monitored at the early stages using some engineering solutions. Therefore, there is a necessity to develop accurate machine learning models for accurate interpretation before applying them in clinical trials. Hence, the proposed work has developed a model to diagnose monkey pox at the best accurate levels for accurate interpretation. The proposed enhanced convolutional neural network model is compared with the exisiting approaches. The obtained results were compared and indicate the superiority of the proposed algorithm.
Co-Authors Anilloy Frank Sultan Saleem Khalaf Al Hattali Syed Ghouse