The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. IoT is one of the fastest developing fields in the history of computing, with an estimated 50 billion devices by the end of 2020. However, the crosscutting nature of IoT systems and the multidisciplinary components involved in the deployment of such systems have introduced new security challenges. Implementing security measures, such as encryption, authentication, access control, network and application security for IoT devices and their inherent vulnerabilities is ineffective. Therefore, existing security methods should be enhanced to effectively secure the IoT ecosystem. Machine learning and deep learning (ML/DL) have advanced considerably over the last few years, and machine intelligence has transitioned from laboratory novelty to practical machinery in several important applications. Consequently, ML/DL methods are important in transforming the security of IoT systems from merely facilitating secure communication between devices to security-based intelligence systems. The goal of this work is to provide a comprehensive survey of ML methods and recent advances in DL methods that can be used to develop enhanced security methods for IoT systems. IoT security threats that are related to inherent or newly introduced threats are presented, and various potential IoT system attack surfaces and the possible threats related to each surface are discussed. We then thoroughly review ML/DL methods for IoT security and present the opportunities, advantages and shortcomings of each method. We discuss the opportunities and challenges involved in applying ML/DL to IoT security. These opportunities and challenges can serve as potential future research directions.

A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security

A review of smart home applications based on Internet of Things

The vision of Industry 4.0, otherwise known as the fourth industrial revolution, is the integration of massively deployed smart computing and network technologies in industrial production and manufacturing settings for the purposes of automation, reliability, and control, implicating the development of an Industrial Internet of Things (I-IoT). Specifically, I-IoT is devoted to adopting the IoT to enable the interconnection of anything, anywhere, and at any time in the manufacturing system context to improve the productivity, efficiency, safety, and intelligence. As an emerging technology, I-IoT has distinct properties and requirements that distinguish it from consumer IoT, including the unique types of smart devices incorporated, network technologies and quality-of-service requirements, and strict needs of command and control. To more clearly understand the complexities of I-IoT and its distinct needs and to present a unified assessment of the technology from a systems’ perspective, in this paper, we comprehensively survey the body of existing research on I-IoT. Particularly, we first present the I-IoT architecture, I-IoT applications (i.e., factory automation and process automation), and their characteristics. We then consider existing research efforts from the three key system aspects of control, networking, and computing. Regarding control, we first categorize industrial control systems and then present recent and relevant research efforts. Next, considering networking, we propose a three-dimensional framework to explore the existing research space and investigate the adoption of some representative networking technologies, including 5G, machine-to-machine communication, and software-defined networking. Similarly, concerning computing, we again propose a second three-dimensional framework that explores the problem space of computing in I-IoT and investigate the cloud, edge, and hybrid cloud and edge computing platforms. Finally, we outline particular challenges and future research needs in control, networking, and computing systems, as well as for the adoption of machine learning in an I-IoT context.

A Survey on Industrial Internet of Things: A Cyber-Physical Systems Perspective

Background: Health care providers are adopting information and communication technologies (ICTs) to enhance their services. Telemedicine is one of the services that rely heavily on ICTs to enable remote patients to communicate with health care professionals; in this case, the patient communicates with the health care professional for a follow-up or for a consultation about his or her health condition. This communication process is referred to as an e-consultation. In this paper, telemedicine services refer to health care services that use ICTs, which enable patients to share, transfer, and communicate data or information in real time (ie, synchronous) from their home with a care provider—normally a physician—at a clinical site. However, the use of e-consultation services can be positively or negatively influenced by external or internal factors. External factors refer to the environment surrounding the system as well as the system itself, while internal factors refer to user behavior and motivation.
Objective: This review aims to investigate the barriers and the facilitators that influence the use of home consultation systems in the health care context. This review also aims to identify the effectiveness of Home Online Health Consultation (HOHC) systems in improving patients’ health as well as their satisfaction with the systems.
Methods: We conducted a systematic literature review to search for articles—empirical studies—about online health consultation in four digital libraries: Scopus, Association for Computing Machinery, PubMed, and Web of Science. The database search yielded 2518 articles; after applying the inclusion and exclusion criteria, the number of included articles for the final review was 45. A qualitative content analysis was performed to identify barriers and facilitators to HOHC systems, their effectiveness, and patients’ satisfaction with them.
Results: The systematic literature review identified several external and internal facilitators and barriers to HOHC systems that were used in the creation of a HOHC framework. The framework consists of four requirements; the framework also consists of 17 facilitators and eight barriers, which were further categorized as internal and external influencers on HOHC.
Conclusions: Patients from different age groups and with different health conditions benefited from remote health services. HOHC via video conferencing was effective in delivering online treatment and was well-accepted by patients, as it simulated in-person, face-to-face consultation. Acceptance by patients increased as a result of online consultation facilitators that promoted effective and convenient remote treatment. However, some patients preferred face-to-face consultation and showed resistance to online consultation. Resistance to online consultation was influenced by some of the identified barriers. Overall, the framework identified the facilitators and barriers that positively and negatively influenced the uptake of HOHC systems, respectively.

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Barriers and Facilitators That Influence Telemedicine-Based, Real-Time, Online Consultation at Patients’ Homes: Systematic Literature Review

Survey on blockchain for Internet of Things

This paper presents an approach to incorporate strong security in deploying Internet of Things (IoT) for smart home system, together with due consideration given to user convenience in operating the system. The IoT smart home system runs on conventional wifi network implemented based on the AllJoyn framework, using an asymmetric Elliptic Curve Cryptography to perform the authentications during system operation. A wifi gateway is used as the center node of the system to perform the system initial configuration. It is then responsible for authenticating the communication between the IoT devices as well as providing a mean for the user to setup, access and control the system through an Android based mobile device running appropriate application program.

Securing IoT for smart home system

This paper describes the various issues related to the analog-to-digital (A-D) conversion process performed in a software defined radio (SDR). An architecture that may be suitable for the digital front end of a multiband, multimode SDR is proposed. Implementation considerations based on current analog-to-digital converter (ADC) technologies are discussed, together with digital signal processing techniques that can be applied to enhance the A-D process. Combination of time-interleaved ADCs with multirate polyphase filters banks to perform the channelization while reducing the matching difficulties encountered in time-interleaved ADC systems is also suggested.

ADC systems for SDR digital front-end

With the popularity of using Linux for embedded systems, its real-time performance is increasingly becoming an importance issue for applications that require short latency and task execution predictability as commonly encountered in many embedded systems. This paper presents a survey of the approaches used by commercial vendors and open source community to enhance the real-time performance of the Linux kernel. It outlines some of the main factors that affect the real-time performance of the Linux kernel and describes the two general approaches that are used to improve the real-time performance of the kernel, follows by a comparative study of the various real-time enhanced versions of the Linux that are created for embedded systems.

Real-Time Enhancements for Embedded Linux

This paper presents the methodologies taken to integrate open-source LIVE555 based data streamer with a baseline H.264 encoder running on the Texas Instruments's DaVinci based embedded platform. The system implemented is able to stream live H.264 encoded video over the network, and be displayed on remote stations using the VLC media player. The system developed provides an embedded platform to implement a smart surveillance camera system, whereby video analysis can be performed locally on the embedded platform to minimize the streaming throughput by making use of the H.264 motion vector information.

Implementation of an embedded H.264 live video streaming system

This paper describes the continuous development of a digital map system presented in previous ISCE conferences. The latest version incorporates a number of new features that improve upon the performance of the previous systems. The most significant change is the use of the SVG format to replace the customised XML format used for the display of the digital maps. New techniques are employed in the encoding of the map to further enhance the flexibility of the system. A new client program based on Java's Batik toolkit is also developed to take full advantages of the SVG features in rendering the digital map for display.

N. Vun

Papers

Securing IoT for smart home system

ADC systems for SDR digital front-end

Real-Time Enhancements for Embedded Linux

Implementation of an embedded H.264 live video streaming system

Digital Map System with SVG Display