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Payment methods using mobile devices instead of using traditional methods (cash, credit card, etc) has been gaining popularity all over the world. The ubiquitous nature of smartphones and tablets has widened the ambit for using these devices for payments and other daily life activities. Recent advancements in mobile technology along with the convenience of mobile devices made these applications possible. Despite the worldwide user adoption of mobile applications, security is the key challenge in mobile banking and payments system. Mobile payments systems need to be very efficient and provide utmost security endlessly. State-of-the-art mobile payment systems need the physical presence of a merchant agent to make a payment. In this article, we had described in detail about the design and implementation of a mobile payments application, used to make in-store purchases and make secure payments without any physical presence of a cashier or a merchant agent. We proposed a novel privacy-preserving and secure authentication algorithm to make mobile payments using biometrics. The analysis and experimental results show the reliability and efficiency of our proposed solution.

In a distributed cloud, unlike centralized resource management, users provide and share resources. However, this allows for the existence of free riders who do not provide resources to others, but at the same time use resources that others provide. In a distributed cloud, resource providers share resources in a P2P fashion. In this paper, we propose a 3-pronged solution KeyPIn—a Key-based, Participation-based, and Incentive-based scheme to mitigate the free rider problem in a distributed cloud environment. We propose an incentive-based scheme based on game theory for providers to participate in the cloud by providing resources. This participation will be low for free riders thereby limiting their access to resources. A secure time instant key is generated based on a key management scheme that enables good users’ more time to access resources as their participation is high, whereas free riders are given limited or no time as their participation is low. Simulation results show that our scheme is effective in mitigating the free rider problem in the distributed cloud.

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BackgroundLinking medical records across different medical service providers is important to the enhancement of health care quality and public health surveillance. In records linkage, protecting the patients’ privacy is a primary requirement. In real-world health care databases, records may well contain errors due to various reasons such as typos. Linking the error-prone data and preserving data privacy at the same time are very difficult. Existing privacy preserving solutions for this problem are only restricted to textual data.ObjectiveTo enable different medical service providers to link their error-prone data in a private way, our aim was to provide a holistic solution by designing and developing a medical record linkage system for medical service providers.MethodsTo initiate a record linkage, one provider selects one of its collaborators in the Connection Management Module, chooses some attributes of the database to be matched, and establishes the connection with the collaborator after the negotiation. In the Data Matching Module, for error-free data, our solution offered two different choices for cryptographic schemes. For error-prone numerical data, we proposed a newly designed privacy preserving linking algorithm named the Error-Tolerant Linking Algorithm, that allows the error-prone data to be correctly matched if the distance between the two records is below a threshold.ResultsWe designed and developed a comprehensive and user-friendly software system that provides privacy preserving record linkage functions for medical service providers, which meets the regulation of Health Insurance Portability and Accountability Act. It does not require a third party and it is secure in that neither entity can learn the records in the other’s database. Moreover, our novel Error-Tolerant Linking Algorithm implemented in this software can work well with error-prone numerical data. We theoretically proved the correctness and security of our Error-Tolerant Linking Algorithm. We have also fully implemented the software. The experimental results showed that it is reliable and efficient. The design of our software is open so that the existing textual matching methods can be easily integrated into the system.ConclusionsDesigning algorithms to enable medical records linkage for error-prone numerical data and protect data privacy at the same time is difficult. Our proposed solution does not need a trusted third party and is secure in that in the linking process, neither entity can learn the records in the other’s database.