Multifactor Authentication in Automated Teller Machine

Skimming of card details is the primary problem faced by many people in today’s world. This can be done in many ways. For instance, a thief can insert a small device into the machine and steal the information. When a person swipes or inserts a card, the details will be captured and stored. This problem can be solved using biometrics. Biometrics include fingerprint, iris, face, retina scanning, etc. This paper focused on solving this issue using fingerprint and iris recognition using OpenCV and propose a suitable method for this issue. Fingerprint and iris recognition are performed by identifying the keypoints and descriptors and matching those with the test data. Keywords: Biometrics, Fingerprint recognition, Iris recognition, Scale Invariant Feature Transform, Oriented FAST and Rotated BRIEF, OpenCV

Presence of SARS-CoV-2 in food surfaces and public space surfaces in 3 districts of Lima, Peru.

Objective: The goal of this study is to determine the presence of SARS-CoV-2 in food surfaces and public space surfaces in 3 districts of Lima, Peru. Material and methods: Cross-sectional descriptive study, carried out in the districts of San Juan de Lurigancho, San Martin de Porres and Villa el Salvador. Surfaces that were exposed to the greatest user manipulation were selected, samples were swabbed for 4 weeks and transported to the laboratory to determine the presence of the virus. Results: 1095 inert surface samples and 960 food surface samples were evaluated for the identification of SARS-CoV-2 by the RT-PCR molecular test, whereby only one sample from an ATM (Automated Teller Machine) was positive. Conclusions: Most of the inert and food surfaces evaluated did not show the presence of SARS-CoV-2 during the time of sample collection. Despite the negative results, the frequency of disinfection measures should be maintained and increased, especially on inert high-contact surfaces, and hygiene measures on food should be continue.

Financial Technology as Determinants of Bank Profitability

This study analyzes the influence of financial technology on the financial performance of banks listed on the Indonesia Stock Exchange (IDX) during the 2014-2020 period. Financial technology was measured by the number of Automated Teller Machine (ATM) transactions and internet and mobile banking, while bank profitability was measured by Return On Assets (ROA). Furthermore, this study used the panel data regression analysis, with the Automated Teller Machine (ATM) transactions as well as internet and mobile banking as the independent variables, and ROA as the dependent variable. Purposive sampling was used to select six banks as samples. The results showed the fixed effect as the most suitable model, where ROA is affected by the internet and mobile banking, while the TM technology has no effect.

Nature of frauds in Nigeria’s banking ecosystem, 2015-2019

Purpose This paper aims to examine the nature of frauds and insider involvement in the perpetration of frauds in Nigeria’s banking ecosystem. It probes the payment platforms mostly vulnerable to fraud attacks since the role-out of cashless policy in Nigeria in 2014. Design/methodology/approach Using secondary data on frauds and forgeries in Nigeria Deposit Insurance Corporation annual report of 2019, the study engaged the data on frauds and forgeries to unpack the complex dynamics in relation to bank frauds in Nigeria. Findings Findings show that fraud attacks on deposit money banks increased year in year out although the actual monetary loss dropped in 2019 as against 2018. Technology mediated transactions such as the use of automated teller machine and internet-based transactions experienced the most fraud. In relation to the role of insiders, all cadres of staff were involved in the fraud but majority of those involved were temporary staff. Practical implications Arising from this, it is suggested that banks should continue to strengthen security system and governance structures. Employing temporary staff should be phased out while online and offline vigilance should be mounted. Originality/value The study contributes to knowledge by examining the nature of frauds and unveiling the insider dimensions of fraud and the possible factors increasing the vulnerability of casual staff to perpetrate fraud.

Automated Teller Machine-Based Voting System

Voting is a critical element of any election which involves the processes of electing leaders or representatives into positions of authority in a democratic system of government. In most developing countries of the world, this process is usually marred with challenges of confidentiality, integrity, availability and auditability such as falsification of results, identity theft, theft of ballot boxes, multiple voting problems, over voting, and electoral fraud. This paper presents a framework for Automated Teller Machine-based voting system that solves the aforementioned challenges of the current voting system by using the existing Automated Teller Machines and debit cards issued for voting. Going further to implement the solution proposed in this paper will enhance and guarantee the credibility of the electoral processes and show a true reflection of the wishes of the people.

Design and Implementation of Multilayer Security for ATM Machines

Automated teller machine (ATM) nowadays are a favourite spot for attackers as they are available everywhere and are much easier to rob. Generally, ATM attacks can be either physical ATM attacks or ATM-related fraud attacks. In this paper the idea of an ATM system with multilayer security is proposed with the help of internet of things (IoT), fingerprint identification and face recognition to increase the security of ATM. The physical ATM counter attacks can be identified by using specific sensors to detect changes in vibration and temperature in the ATM counter. To prevent ATM related fraud attacks the proposed system has additional security features like fingerprint identification and face recognition along with ATM number verification. The convolutional neural network (CNN) and machine learning based face recognition is used in this work which is quite reliable. Failures in any of the above steps cancel the transactions and so the proposed system provides multi layer security which makes it impossible for the attackers to break the ATM security. The proposed system will help to increase the security of the ATM and provide safe and secure ATM transactions.

Bacteriological Assessment of Automated Teller and Point of Sales Machine User Interface in Uyo Metropolis, Nigeria

The Automated Teller Machine (ATM) and Point of Sales (POS) machine user interface of different banks, schools, hospitals, restaurants/eateries, shopping malls and petrol/gas stations in Uyo metropolis were bacteriologically assessed in the dry and wet seasons using cultural technique. The result of fomites key pads indicate total heterotrophic bacteria counts (THBC) was in the order: Banks > Hospitals > Schools > Petrol/Gas stations > shopping malls > Restaurants/Eateries in both seasons. There was an increase in the bacterial counts of the fomites from all locations in the wet season compared to the dry season and the difference significant (p = 0.05). The THBC from ATMs in banks, hospitals and schools ranged from 5.6 ± 0.1 to 7.8 ± 0.6 Log₁₀CFU/cm2 and from POS 3.4 ± 0.3 to 5.0 ± 0.2 Log₁₀CFU/cm2) for Petrol/Gas stations, shopping malls and Restaurants/Eateries in the wet season. The dry season revealed THBC range of 4.1± 0.6 to 6.4 ± 0.3 Log₁₀CFU/cm2 for ATMs and 2.6 ± 0.8 to 3.8 ± 0.1 Log₁₀CFU/cm2 for POS. Organisms associated with the fomites were Escherichia coli, Staphylococcus aureus, Staphylococcus epidermidis and species of Bacillus, Pseudomonas, Proteus, Streptococcus, Salmonella, Shigella, Micrococcus, Vibrio and Klebsiella. The highest and least frequency of occurrence in the dry season indicated Micrococcus (17.2%) and Vibrio (1.4%) in relation to Staphylococcus aureus (18.2%) and Proteus sp. (2.8%) in the wet season. The Gram-positive organisms exhibited high and low susceptibility to Gentamycin and Augmentin compared to Ofloxacin and Amoxicillin respectively in Gram-negative bacteria. The results indicate ATM and POS machine user interface as possible sources of pathogenic organisms. Therefore, regular cleaning of ATM and POS user interface and public awareness on the need for adequate personal hygienic practice after the use of these machines is recommended to reduce associated risks.