Near Field Communication (NFC) is an emerging short-range wireless communication technology that offers great and varied promise in services such as payment, ticketing, gaming, crowd sourcing, voting, navigation, and many others. NFC technology enables the integration of services from a wide range of applications into one single smartphone. NFC technology has emerged recently, and consequently not much academic data are available yet, although the number of academic research studies carried out in the past two years has already surpassed the total number of the prior works combined. This paper presents the concept of NFC technology in a holistic approach from different perspectives, including hardware improvement and optimization, communication essentials and standards, applications, secure elements, privacy and security, usability analysis, and ecosystem and business issues. Further research opportunities in terms of the academic and business points of view are also explored and discussed at the end of each section. This comprehensive survey will be a valuable guide for researchers and academicians, as well as for business in the NFC technology and ecosystem.

The Survey on Near Field Communication

A trajectory privacy-preserving scheme based on a dual-K mechanism for continuous location-based services

Huang and Wu in [IEEE Transactions on Computers 46 (1997) 484-490] introduced the balanced hypercube $BH_n$ as an interconnection network topology for computing systems, and they proved that $BH_n$ is vertex-transitive. However, some other symmetric properties, say edge-transitivity and arc-transitivity, of $BH_n$ remained unknown. In this paper, we solve this problem and prove that $BH_n$ is an arc-transitive Cayley graph. Using this, we also investigate some reliability measures, including super-connectivity, cyclic connectivity, etc., in $BH_n$ . First, we prove that every minimum edge-cut of $BH_n (n\ge 2)$ isolates a vertex, and every minimum vertex-cut of $BH_n (n\ge 3)$ isolates a vertex. This is stronger than that obtained by Wu and Huang which shows the connectivity and edge-connectivity of $BH_n$ are $2n$ . Second, Yang [Applied Mathematics and Computation 219 (2012) 970-975.] proved that for $n\ge 2$ , the super-connectivity of $BH_n$ is $4n-4$ and the super edge-connectivity of $BH_n$ is $4n-2$ . In this paper, we proved that $BH_n (n\ge 2)$ is super- $\lambda^{\prime }$ but not super- $\kappa^{\prime }$ . That is, every minimum super edge-cut of $BH_n (n\ge 2)$ isolates an edge, but the minimum super vertex-cut of $BH_n (n\ge 2)$ does not isolate an edge. Third, we also obtain that for $n\ge 2$ , the cyclic connectivity of $BH_n$ is $4n-4$ and the cyclic edge-connectivity of $BH_n$ is $4(2n-2)$ . That is, to become a disconnected graph which has at least two components containing cycles, we need to remove at least $4n-4$ vertices (resp. $4(4n-2)$ edges) from $BH_n (n\ge 2)$ .

Symmetric Property and Reliability of Balanced Hypercube

Internet of Things (IoT) and smart medical devices have improved the healthcare systems by enabling remote monitoring and screening of the patients' health conditions anywhere and anytime. Due to an unexpected and huge increasing in number of patients during coronavirus (novel COVID-19) pandemic, it is considerably indispensable to monitor patients' health condition continuously before any serious disorder or infection occur. According to transferring the huge volume of produced sensitive health data of patients who do not want their private medical information to be revealed, dealing with security issues of IoT data as a major concern and a challenging problem has remained yet. Encountering this challenge, in this paper, a remote health monitoring model that applies a lightweight block encryption method for provisioning security for health and medical data in cloud-based IoT environment is presented. In this model, the patients' health statuses are determined via predicting critical situations through data mining methods for analyzing their biological data sensed by smart medical IoT devices in which a lightweight secure block encryption technique is used to ensure the patients' sensitive data become protected. Lightweight block encryption methods have a crucial effective influence on this sort of systems due to the restricted resources in IoT platforms. Experimental outcomes show that K-star classification method achieves the best results among RF, MLP, SVM, and J48 classifiers, with accuracy of 95%, precision of 94.5%, recall of 93.5%, and f-score of 93.99%. Therefore, regarding the attained outcomes, the suggested model is successful in achieving an effective remote health monitoring model assisted by secure IoT data in cloud-based IoT platforms.

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A secure remote health monitoring model for early disease diagnosis in cloud-based IoT environment.

A distributed denial of service (DDoS) attack represents a major threat to service providers. More specifically, a DDoS attack aims to disrupt and deny services to legitimate users by overwhelming the target with a massive number of malicious requests. A cyberattack of this kind is likely to result in tremendous economic losses for businesses and service providers due to increasing both operating and financial costs. In recent years, machine learning (ML) techniques have been widely used to prevent DDoS attacks. Indeed, many defense systems have been transformed into smart and intelligent systems through the use of ML techniques, which allow them to defeat DDoS attacks. This paper analyzes recent studies concerning DDoS detection methods that have adapted single and hybrid ML approaches in modern networking environments. Additionally, the paper discusses different DDoS defense systems based on ML techniques that make use of a virtualized environment, including cloud computing, software-defined network, and network functions virtualization environments. As the development of the Internet of Things (IoT) has been the subject of significant research attention in recent years, the paper also discusses ML approaches as security solutions against DDoS attacks in IoT environments. Furthermore, the paper recommends a number of directions for future research. This paper is intended to assist the research community with the design and development of effective defense systems capable of overcoming different types of DDoS attacks.

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Machine Learning Approaches for Combating Distributed Denial of Service Attacks in Modern Networking Environments

In current years, drowsy driver detection is the most necessary procedure to prevent any road accidents, probably worldwide. The aim of this study was to construct a smart alert technique for building intelligent vehicles that can automatically avoid drowsy driver impairment. But drowsiness is a natural phenomenon in the human body that happens due to different factors. Hence, it is required to design a robust alert system to avoid the cause of the mishap. In this proposed paper, we address a drowsy driver alert system that has been developed using such a technique in which the Video Stream Processing (VSP) is analyzed by eye blink concept through an Eye Aspect Ratio (EAR) and Euclidean distance of the eye. Face landmark algorithm is also used as a proper way to eye detection. When the driver’s fatigue is detected, the IoT module issues a warning message along with impact of collision and location information, thereby alerting with the help of a voice speaking through the Raspberry Pi monitoring system.

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IoT-Based Smart Alert System for Drowsy Driver Detection

Among other security concerns, the reliable device to device direct communication is an important research aspect in sensor cloud system application of Internet of things (IoT). The access control mechanism can ensure the reliability through secure communication among two IoT devices without mediation of intermediate agent. Mainly, it requires twofold strategy involving the authentication of each other and session key establishment. Quite recently, in 2019, Das et al. proposed a certificate based lightweight access control and key agreement scheme for IoT devices (LACKA-IoT) to ensure smooth and secure access control and claimed LACKA-IoT to withstand the several attacks. Specifically, it is claimed that LACKA-IoT can resist device impersonation and man in middle attacks. However, the proof in this article refutes their claim and it is shown here, that LACKA-IoT is insecure against both device impersonation and man in middle attacks. An adversary just by using public parameters and by listening the communication channel can impersonate any device. Moreover, the same can also launch successful man in middle attack using public parameters and listened messages from public channel. An improved protocol iLACKA-IoT is then proposed in the paper. The iLACKA-IoT provides resistance against various types of threats and provides the required level of security, for evidence both formal validation through random or real (ROR) model as well as the informal validation through discussion on attack resilience is provided. The iLACKA-IoT is not only better in security but also provides performance efficiency as compared with LACKA-IoT and related schemes.

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A Secure and Reliable Device Access Control Scheme for IoT Based Sensor Cloud Systems

HPSIPT: A high-precision single-packet IP traceback scheme

The hypercube is a popular interconnection network for multiprocessor systems. The balanced hypercube, denoted by BH n , is a variant of the hypercube network. The balanced hypercube reserves some properties of the hypercube and enhances some other properties of it as well. For a multiprocessor system, the reliability of an interconnection network is a major concern. It is well-known that connectivity is a important measure for the reliability of an interconnection network. In this paper, we study a refined reliability measure, called super connectivity, of the balanced hypercube. We show that the super connectivity of BH n is 4n − 4 for n ≥ 2. That is, at least 4n − 4 vertices need to be removed from BH n to get a disconnected graph which contains no isolated vertex.

Reliability analysis of balanced hypercubes

In 2014, Yang proposed a method to enhance the current EMV credit card protocol (EPMAR). However, the protocol ignores the exceeding of a credit quota caused by multiple offline transactions, with the result that the amount spent can exceed the risk control scope. In this paper, we proposed an EMV-compatible offline mobile payment protocol with mutual authentication (EOPMA) to enhance EPMAR. In EOPMA, we use the reverse hash chain technique to guarantee the payment, which solves the problem of credit quotas getting exceeded because of multiple offline payments. During a transaction, in addition to payment for merchandise, an offline authorization certificate for the transaction is sent to the merchant. The merchant can verify the correctness of the transaction in real time. Our protocol is compatible with the EMV standard, which is applicable to the retail environment of numerous merchants and effectively, making EMV transactions more secure and reliable. We use numerical analysis to examine the security and performance of the protocols. We formally check the correctness of EOPMA by using the Gong–Needham–Yahalom logic.

https://www.mdpi.com/1424-8220/19/21/4611/pdf

Ming-Hour Yang

Papers

IoT-Based Smart Alert System for Drowsy Driver Detection

A Secure and Reliable Device Access Control Scheme for IoT Based Sensor Cloud Systems

HPSIPT: A high-precision single-packet IP traceback scheme

Reliability analysis of balanced hypercubes

EMV-Compatible Offline Mobile Payment Protocol with Mutual Authentication.