The Internet of Things (IoT)-centric concepts like augmented reality, high-resolution video streaming, self-driven cars, smart environment, e-health care, etc. have a ubiquitous presence now. These applications require higher data-rates, large bandwidth, increased capacity, low latency and high throughput. In light of these emerging concepts, IoT has revolutionized the world by providing seamless connectivity between heterogeneous networks (HetNets). The eventual aim of IoT is to introduce the plug and play technology providing the end-user, ease of operation, remotely access control and configurability. This paper presents the IoT technology from a bird’s eye view covering its statistical/architectural trends, use cases, challenges and future prospects. The paper also presents a detailed and extensive overview of the emerging 5G-IoT scenario. Fifth Generation (5G) cellular networks provide key enabling technologies for ubiquitous deployment of the IoT technology. These include carrier aggregation, multiple-input multiple-output (MIMO), massive-MIMO (M-MIMO), coordinated multipoint processing (CoMP), device-to-device (D2D) communications, centralized radio access network (CRAN), software-defined wireless sensor networking (SD-WSN), network function virtualization (NFV) and cognitive radios (CRs). This paper presents an exhaustive review for these key enabling technologies and also discusses the new emerging use cases of 5G-IoT driven by the advances in artificial intelligence, machine and deep learning, ongoing 5G initiatives, quality of service (QoS) requirements in 5G and its standardization issues. Finally, the paper discusses challenges in the implementation of 5G-IoT due to high data-rates requiring both cloud-based platforms and IoT devices based edge computing.

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Internet of Things (IoT) for Next-Generation Smart Systems: A Review of Current Challenges, Future Trends and Prospects for Emerging 5G-IoT Scenarios

Pervasive growth of Internet of Things (IoT) is visible across the globe. The 2016 Dyn cyberattack exposed the critical fault-lines among smart networks. Security of IoT has become a critical concern. The danger exposed by infested Internet-connected Things not only affects the security of IoT but also threatens the complete Internet eco-system which can possibly exploit the vulnerable Things (smart devices) deployed as botnets. Mirai malware compromised the video surveillance devices and paralyzed Internet via distributed denial of service attacks. In the recent past, security attack vectors have evolved bothways, in terms of complexity and diversity. Hence, to identify and prevent or detect novel attacks, it is important to analyze techniques in IoT context. This survey classifies the IoT security threats and challenges for IoT networks by evaluating existing defense techniques. Our main focus is on network intrusion detection systems (NIDSs); hence, this paper reviews existing NIDS implementation tools and datasets as well as free and open-source network sniffing software. Then, it surveys, analyzes, and compares state-of-the-art NIDS proposals in the IoT context in terms of architecture, detection methodologies, validation strategies, treated threats, and algorithm deployments. The review deals with both traditional and machine learning (ML) NIDS techniques and discusses future directions. In this survey, our focus is on IoT NIDS deployed via ML since learning algorithms have a good success rate in security and privacy. The survey provides a comprehensive review of NIDSs deploying different aspects of learning techniques for IoT, unlike other top surveys targeting the traditional systems. We believe that, this paper will be useful for academia and industry research, first, to identify IoT threats and challenges, second, to implement their own NIDS and finally to propose new smart techniques in IoT context considering IoT limitations. Moreover, the survey will enable security individuals differentiate IoT NIDS from traditional ones.

Network Intrusion Detection for IoT Security Based on Learning Techniques

A Comprehensive Survey on Attacks, Security Issues and Blockchain Solutions for IoT and IIoT

Today is the era of the Internet of Things (IoT). The recent advances in hardware and information technology have accelerated the deployment of billions of interconnected, smart and adaptive devices in critical infrastructures like health, transportation, environmental control, and home automation. Transferring data over a network without requiring any kind of human-to-computer or human-to-human interaction, brings reliability and convenience to consumers, but also opens a new world of opportunity for intruders, and introduces a whole set of unique and complicated questions to the field of Digital Forensics. Although IoT data could be a rich source of evidence, forensics professionals cope with diverse problems, starting from the huge variety of IoT devices and non-standard formats, to the multi-tenant cloud infrastructure and the resulting multi-jurisdictional litigations. A further challenge is the end-to-end encryption which represents a trade-off between users’ right to privacy and the success of the forensics investigation. Due to its volatile nature, digital evidence has to be acquired and analyzed using validated tools and techniques that ensure the maintenance of the Chain of Custody. Therefore, the purpose of this paper is to identify and discuss the main issues involved in the complex process of IoT-based investigations, particularly all legal, privacy and cloud security challenges. Furthermore, this work provides an overview of the past and current theoretical models in the digital forensics science. Special attention is paid to frameworks that aim to extract data in a privacy-preserving manner or secure the evidence integrity using decentralized blockchain-based solutions. In addition, the present paper addresses the ongoing Forensics-as-a-Service (FaaS) paradigm, as well as some promising cross-cutting data reduction and forensics intelligence techniques. Finally, several other research trends and open issues are presented, with emphasis on the need for proactive Forensics Readiness strategies and generally agreed-upon standards.

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A Survey on the Internet of Things (IoT) Forensics: Challenges, Approaches, and Open Issues

As an emerging technology, the Internet of Things (IoT) revolutionized the global network comprising of people, smart devices, intelligent objects, data, and information. The development of IoT is still in its infancy and many related issues need to be solved. IoT is a unified concept of embedding everything. IoT has a great chance to make the world a higher level of accessibility, integrity, availability, scalability, confidentiality, and interoperability. However, how to protect IoT is a challenging task. System security is the foundation for the development of IoT. This article systematically reviews IoT cybersecurity. The key considerations are the protection and integration of heterogeneous smart devices and information communication technologies (ICT). This review provides useful information and insights to researchers and practitioners who are interested in cybersecurity of IoT, including the current research of IoT cybersecurity, IoT cybersecurity architecture and taxonomy, key enabling countermeasures and strategies, major applications in industries, research trends and challenges.

Internet of Things (IoT) Cybersecurity Research: A Review of Current Research Topics

Industrial Internet of Things (IIoTs) is the fast growing network of interconnected things that collects and exchange data using embedded sensors planted everywhere. Several IIoT applications such as the ones related to healthcare systems are expected to widely utilize the evolving 5G technology. This 5G-inspired IIoT paradigm in healthcare applications enables the users to interact with various types of sensors via secure wireless medical sensor networks (WMSNs). Users of 5G networks should interact with each other in a seamless secure manner. And thus, security richness is highly coveted for the real time wireless sensor network systems. Asking users to verify themselves before every interaction is a tedious, time-consuming process that disrupts inhabitants’ activities, and degrades the overall healthcare system performance. To avoid such problems, we propose a context-sensitive seamless identity provisioning (CSIP) framework for the IIoT. CSIP proposes a secure mutual authentication approach using hash and global assertion value to prove that the proposed mechanism can achieve the major security goals of the WMSN in a short time period.

Context-Sensitive Access in Industrial Internet of Things (IIoT) Healthcare Applications

Industrial Internet of Things (IIoTs) is the fast growing network of interconnected things that collect and exchange data using embedded sensors planted everywhere. It is an interconnection of several things through a diverse communication system capable of monitoring, collecting, exchanging, analysing, and delivering valuable and challenging amount of information. Given their ability to be operated autonomously, their high mobility, and their communication and processing power, Unmanned Aerial Vehicles (UAVs) are expected to be involved in numerous IIoT-related applications, where multimedia and video streaming plays a key role. Our main interest is the multimedia routing in IIoT and its facilities during and/or after operational hours. For recovering, constructing and selecting k-disjoint paths, capable of putting up with failure of the parameters but satisfying the quality of service, we introduce an industry-oriented Canonical Particle Swarm (CPS) optimization data delivery framework. During communication with the UAV, multi-swarm strategy is used to determine the optimal direction while performing a multipath routing. Authenticity of the proposed approach has been tested and results show that, compared to the ordinary Canonical Particle Multi-path Swarm (CPMS) optimization and Fully Multi-path Particle Swarm (FMPS) optimization, the proposed method is better.

5G/IoT-enabled UAVs for multimedia delivery in industry-oriented applications

With the revolution of the Internet technology, smart-sensing applications and the Internet of Things (IoT) are coupled in critical missions. Wireless sensor networks (WSNs), for example, present the main enabling technology in IoT architectures and extend the spectrum of their smart applications. However, this technology has limited resources and suffers from several vulnerabilities and security issues. Since the wireless networks used by this technology are deployed in open areas, several challenges are faced by the service provider in terms of privacy and the quality of service. Encryption can be a good solution to preserve confidentiality and privacy, but it raises serious problems concerning time latency and performance. In this paper, we propose agile framework that enables authentication, confidentiality and integrity while collecting the sensed data by using elliptic curve cryptography.

Confidential smart-sensing framework in the IoT era

The use of drones to perform various task has recently gained a lot of attention. Drones have been used by traders to deliver goods to customers, scientists, and researchers to observe and search for endangered species, and by the military during critical operations. The flexibility of drones in remote controlling makes them ideal candidates to perform critical tasks with minimum time and cost. In this paper, we use drones to setup base stations that provide 5G cellular coverage over a given area in danger. The aim of this paper is to determine the optimum number of drones and their optimum location, such that each point in the selected area is covered with the least cost while considering communication relevant parameters such as data rate, latency, and throughput. The problem is mathematically modeled by forming linear optimization equations. For fast optimized solutions, genetic algorithm (GA) and simulated annealing (SA) algorithms are provisionally employed to solve the problem, and the results are accordingly compared. Using these two meta-heuristic methods, quick and relatively inexpensive feedback can be provided to designers and service providers in 5G next generation networks.

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Enhanced Deployment Strategy for the 5G Drone-BS Using Artificial Intelligence

Energy-efficient retrofits embrace enhancement of the building envelope through climate control strategies, employment of building-integrated renewable energy technologies, and insulation for a sustainable city. Building envelope improvements with insulation is a common approach, yet decision-making plays an important role in determining the most appropriate envelope retrofit strategy. In this paper, the main objective is to evaluate different retrofit strategies (RS) through a calibrated simulation approach. Based on an energy performance audit and monitoring, an existing building is evaluated on performance levels and improvement potentials with basic energy conservation measures. The considered building is experimentally monitored for a full year, and monitoring data are used in calibrating the simulation model. The validation of the base model is done by comparing the simulation analysis with the experimental investigation, and good agreement is found. Three different retrofit strategies based on Intervention of minor (RS1), Moderate (RS2), and Major (RS3) are analyzed and juxtaposed with the base model to identify the optimal strategy of minimizing energy consumption. The result shows that total energy intensity in terms of the percentage reduction index is about 16.7% for RS1, 19.87 for RS2, and 24.12% for RS3. Hence, RS3 is considered the optimal retrofit strategy and is further simulated for a reduction in carbon dioxide (CO2) emissions and payback investigation. It was found that the annual reduction in CO2 emissions of the building was 18.56%, and the payback period for the investment was 10.6 years.

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Sinem Alturjman

Papers

Context-Sensitive Access in Industrial Internet of Things (IIoT) Healthcare Applications

5G/IoT-enabled UAVs for multimedia delivery in industry-oriented applications

Confidential smart-sensing framework in the IoT era

Enhanced Deployment Strategy for the 5G Drone-BS Using Artificial Intelligence

Retrofitting Existing Buildings to Improve Energy Performance