E-payment is the key function for any e-business as it is rising exponentially in today's business world as e-business grows. E-payments made it easier for people to survive and helped them save a lot of money and time. Using various forms and devices, our payments are more exciting and convenient to press on your mobile phone and pay for your orders. In order to obtain better results in e-business, it must be linked to e-payments. E-payments have many systems and opportunities in the field of e-business, but it is facing many risks and challenges. This paper presents an overview study for e-payments opportunities, challenges and different risks for e-payments specially fraud as it is one of the most critical threats to e-payments field and it is causing huge losses. Paper also discusses different types of epayments, benefits and the future of e-payment.
Traffic congestion is a serious problem in many developing countries like Egypt. In the presence of the traditional traffic light system, it creates health risks, wastes time and fuel, and pollutes the air. Therefore, there is a big need for a smart traffic management system. This study contributes in solving this problem by introducing an artificial intelligence-based smart traffic light system using fuzzy logic to ensure the smooth flow of traffic in cities. Research results indicate that smart traffic light management is very crucial in smart cities to reduce their carbon footprint to save the world and save energy. Other possible application could be implemented with minor system upgrades such as Detection and Management of traffic Congestion, Automatic Billing of Toll Charges, Automatic detection of speed limit Violation, Route planning, Intelligent Internet of Vehicles, and Prevention of Road Accidents. Four traffic light approaches (fixed-time, smart-time, fixedtime-fuzzy logic, and smart-time-fuzzy-logic) are developed with different eight traffic scenarios. The four approaches are applied with two tools, the first tool is a real Marquette which consists of 4 roads with only one or two vehicles. The second is a simulation software which consists of 4 roads with more than 100 vehicles through 10 min. Many sensors such as (IR sensors, rain sensors, and LEDs to control traffic light) are used to collect data and then the fuzzy algorithm is used to ensure the smooth flow of traffic in cities. The traffic data acquired from the vehicles is fed into the proposed model to maximize the duration of the green light based on the road state. According to experimental results, the proposed smart fuzzy technique simulation software reduced the average waiting time of the vehicles from 769 to 289 sec in heavy rain condition. It also reduced the total time for all vehicles from 2490 to 1154 sec.
Despite the importance of big data, it faces many challenges. The most important big data challenges are data storage, heterogeneity, inconsistency, timeliness, security, scalability, visualization, fault tolerance, and privacy. This paper concentrates on privacy which is one of the most pressing issues with big data. As mentioned in the Literature Review below there are numerous methods for safeguarding privacy with big data. This paper introduces an efficient technique called Specialized Negative Database (SNDB) for protecting privacy in big data. SNDB is proposed to avoid the drawbacks of all previous techniques. SNDB is based on deceiving bad users and hackers by replacing only sensitive attribute with its complement. Bad user cannot differentiate between the original data and the data after applying this technique.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.