IoT Agent Platform Mechanism with Transparent Cloud Computing Framework for Improving IoT Security

The recent trend in the Internet of Things (IoT) is bringing innovations in almost every field of science. IoT is mainly focused on the connectivity of things via the Internet. IoT’s integration tools are developed based on the Do It Yourself (DIY) approach, as the general public lacks technical skills. This paper presents a thermal comfort system based on tasks allocation mechanism in smart homes. This paper designs and implements the tasks allocation mechanism based on virtual objects composition for IoT applications. We provide user-friendly drag and drops panels for the new IoT users to visualize both task composition and device virtualization. This paper also designs tasks generation from microservices, tasks mapping, task scheduling, and tasks allocation for thermal comfort applications in smart home. Microservices are functional units of services in an IoT environment. Physical devices are registered, and their corresponding virtual objects are initialized. Tasks are generated from the microservices and connected with the relevant virtual objects. Afterward, they are scheduled and finally allocated on the physical IoT device. The task composition toolbox is deployed on the cloud for users to access the application remotely. The performance of the proposed architecture is evaluated using both real-time and simulated scenarios. Round trip time (RTT), response time, task dropping and latency are used as the performance metrics. Results indicate that even for worst-case scenarios, values of these metrics are negligible, which makes our architecture significant, better and ideal for task allocation in IoT network.

Research Article| March 01, 2016 The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation Frank Sepulveda; Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Jay Pulliam Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Author and Article Information Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Publisher: Seismological Society of America First Online: 14 Jul 2017 Online Issn: 1938-2057 Print Issn: 0895-0695 © 2016 by the Seismological Society of America Seismological Research Letters (2016) 87 (2A): 345–357. https://doi.org/10.1785/0220150234 Article history First Online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Frank Sepulveda, Jay Pulliam; The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation. Seismological Research Letters 2016;; 87 (2A): 345–357. doi: https://doi.org/10.1785/0220150234 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search ABSTRACT The proliferation of commercial Internet of Things (IoT) devices is raising consumers’ awareness of the benefits of enhancing everyday objects with the ability to communicate, sense, and process information. Commercial‐off‐the‐shelf (COTS) versions of the embedded technologies responsible for the rise of the IoT are easy‐to‐use, inexpensive, and relatively powerful. IoT Makers, technological do‐it‐yourself enthusiasts, utilize these technologies and the IoT ecosystem to create IoT devices that range from casual hobbyist to entrepreneurial in nature.In an effort to develop a “no‐engineer‐needed” Internet of Geophysical Things (IoGT) device, we integrated a COTS embedded computer with a geoscience‐related COTS data acquisition system (DAS). Using skills common to geoscientists, we integrated the Raspberry Pi System‐On‐Chip with the REF TEK (a Trimble brand) 130‐01 DAS. This Raspberry Pi enhanced REF TEK (RaPiER) provides IoGT Makers a platform for the development of geoscientific sensor node or network enhancements. IoGT Makers can use the RaPiER to tinker with IoT capabilities while simultaneously acquiring research‐quality data. Geoscientific (i.e., seismic) application areas that may benefit from RaPiER, particularly RaPiER nodal processing, include earthquake and engineering seismology.In this article, we discuss the emerging technologies that allow IoGT Makers to build their own IoGT device. We review our selection of the Raspberry Pi and REF TEK 130‐01 for IoGT device integration. We provide a RaPiER system integration guide and REF TEK interface software compiled for the Raspberry Pi ( available in the electronic supplement to this article). We present methods to expand RaPiER capabilities using the Raspberry Pi’s ecosystem. Last, we discuss our evaluation of RaPiER’s performance and its suitability for realistic field deployments. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Internet of Things (IoT) becomes more popular, and things are connected to each other through wired or wireless communication methods. Though things are connected with various methods easily, it attracts network attackers who exploit these open and convenient network connections in order to obtain unjustified information and benefits or to subvert various IoT systems. Especially, Denial of Service (DoS) attack becomes a serious problem on IoT system where huge number of devices are connected to. These devices are usually connected to IoT gateways in order to send packets to Internet. However, currently the impact of DoS attack on an IoT gateway, which has various interfaces such as wireless LAN interface and wired LAN interface, is not well examined. In this paper, we assess the impact of DoS attack on an IoT gateway with various scenarios. We implemented a prototype of an IoT gateway which has wired and wireless network interfaces by using Raspberry Pi, OpenWRT, and OVS (Open vSwitch). With this prototype, we evaluated various DoS attack scenarios on this IoT gateway. Through this evaluation, we observed the severity of DoS attack on IoT gateways, especially for wireless connections.

The Internet of Things (IoT) is a fast-expanding network of smart heterogeneous objects. It refers to the physical devices that are capable of communicating with other physical devices. Unlike the wireless sensor networks (WSNs), IoT is connected to worldwide Internet that exposes it to global intrusion in addition to wireless attacks inside an IoT network. It is protected by cryptographic and network security techniques, but they are vulnerable to internal and external attacks. The IoT devices are resource constrained in terms of limited storage, battery, limited transmission range and processing. To protect these tiny devices from the inside and outside cyberattacks, we need a lightweight security system that can run efficiently and effectively on these IoT devices. We also need a system, which can identify the type of intrusion and trigger an alarm in intrusion scenario to take appropriate preventive measure. Hence, an Intrusion Detection System (IDS) plays an important role to prevent such cyberattacks in IoT. These devices can be static or mobile in an IoT environment; this must be considered while designing IDS for IoT system. This book chapter presents various IDSs for an IoT system and their comparisons in terms of detection rate, false positive and accuracy in both static and mobility of devices.

The Internet of Things (IoT) as an important technology consists of a heterogeneous and huge number of devices that generates an enormous amount of data in various applications. However, generating and transmitting huge amount of data in the IoT makes it crucial to implement a secure and safe data transmission scheme. Cryptography methods can secure the confidentiality, data integrity, access control, and authentication. Due to constrained resources in IoT devices, providing classical cryptography schemes isn’t efficient for IoT applications, so a lightweight cryptography scheme is one of the most important solutions to overcome security challenges in IoT. In this paper, a new security scheme called ECCCSASHA256 based on Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm (SHA-256) using Crow Search Algorithm (CSA) has been proposed for secure data transmission in IoT devices. The ECCCSASHA256 model uses the CSA for generating a private key to encode the elliptic curve. Furthermore, the proposed scheme uses SHA-256 model for hashing the incoming encoded data using ECC. The simulation results indicate that the average throughput of the proposed model was about 8.22% and 8.97% higher in encryption and 8.72% and 9.81% higher in decryption compared to 3DES&ECC&SHA-256 and RC4&ECC&SHA-256, respectively.

Usually, IoT devices are designed to perform specific tasks, while robots have to adapt to unpredictable situations. Artificial intelligence and machine learning help these robots cope with the emerging unexpected conditions. The Internet of Robotic Things is an evolving concept that brings together all-encompassing sensors and devices with robotic and autonomous systems. Both IoT devices and robots rely on sensors to understand the surrounding environment, to process data quickly, and to decide how to respond. Nevertheless, while most IoT systems can handle only well-defined tasks, robots can handle expected situations as well. The Internet of Robotic Things is a better Internet of Things (IoT) solution due to its ability to bridge the gap between IT and real operations. The IoRT may face several challenges in power consumption and network bandwidth limitation due to the growth in the information dissemination over the Robotic network. The main objective of this paper is to introduce an overview of the concepts and challenges in the Internet of Robotic Things based on Fog Computing technique. Further, a framework of Fog based IoRT is introduced.

The Internet of Things (IoT) contributes to the advancement and optimization of systems in different contexts by reducing human effort, cost, and time. It is estimated that by 2020 there will be more than 20 billion connected IoT devices. Though justified by emerging IoT applications, such growth requires the implementation of more robust, and consequently, more complex IoT systems. Hence, the optimization of IoT hardware and software design is fundamental towards achieving scalability. It allows for the control and capture of increased data from more connected devices. For this purpose, this work analyzes and compares the scalability of three architectures for IoT devices abstraction of IoT management platforms, and for this, two experiments were carried out. The results show that the Architecture NxN has made better use of computing resources, obtained the average latency value close to zero and connected 100,000 physical emulated devices. Also, being the most optimized architecture for IoT device abstraction of IoT management platforms, in the context of big data, it works in real time.

Internet of Things (IOT) visualizes a future of anything anywhere by anyone at any time. The Information and communication technologies help in creating a revolution in digital technology. IOT are known for interconnecting various physical devices with the networks. In IOT, various physical devices are embedded with different types of sensors and other devices to exchange data between them. An embedded system is a combination of software and hardware where they are programmed for functioning specific functions. These data can be accessed from any parts of the world by making use of cloud. This can be used for creating a digital world, smart homes, healthcare systems and real life data exchange like smart banking. Though Internet of things has emerged long back, it is now becoming popular and gaining attention lately. In healthcare industry, some of the hospitals started using sensors implemented in the bed to get the status of patient's movement and other activities. This paper contains various IOT applications and the role of IOT in the healthcare system, challenges in the healthcare system using IOT. Also, introduced a secured surveillance monitoring system for reading and storing patient's details using low power for transmitting the data.

In future industrial environments, the Internet of things (IoT) paradigm will be leveraged to monitor the activity of assets to thereby enhance the productivity and agility of an enterprises performance. In the IoT concept, any physical object can be incorporated into the IoT and connected to the Internet. Thus, the IoT will comprise a wide range of heterogeneous devices, each using its own protocol for the exchange of data. The incorporation of such a large number of heterogeneous entities within the IoT system represents a challenge to the successful implementation of a complete IoT solution. To solve the heterogeneity problem in the IoT domain, an architecture must be developed that bridges the gap between the physical devices and the higher levels of IoT services. In this paper, we propose an ontological approach that integrates devices featuring a variety of different protocols and establishes connectivity within the IoT ecosystem.

Internet of Things (IoT) have opened the door to a world of unlimited possibilities for implementations in varied sectors in society, but it also has many challenges. One of those challenges is security and privacy. IoT devices are more susceptible to security threats and attacks. Due to constraints of the IoT devices such as area, power, memory, etc., there is a lack of security solutions that are compatible with IoT devices and applications, which is leading this world of securely connected things to the “internet of insecure things.” A promising solution to this problem is going beyond the standard or classical techniques to implementing the security solutions in the hardware of the IoT device. The integration of emerging technologies in IoT networks, such as machine learning, blockchain, fog/edge/cloud computing, and quantum computing have added more vulnerable points in the network. This paper introduces a comprehensive study on IoT security threats and solutions. Additionally, this survey outlines how emerging technologies such as machine learning and blockchain are integrated in IoT, challenges resulted from this integration, and potential solutions to these challenges. The paper utilizes the 4-layer IoT architecture as a reference to identify security issues with corresponding solutions.

Internet of Things (IoT) is the extension of the Internet into everyday objects and physical devices. The IoT is expeditiously becoming ubiquitous. However, independent nodes and customized agreements in use, the privacy of data, coerce IoT security, being an upcoming agitation. These systems should be rated for their efficiency in heterogeneous networks and a wide range of protocols. IoT can be represented as a model with three layers of phases: Perception, movement, and functionality. Within security areas specifically, the lack of these standardization techniques creates issues to develop generalized research solutions to govern what needs to be protected. The challenges can be categorized according to their (IoT applications) usage as domestic, industrial, financial, etc. However, technical implementation and issues related to it are not the only concerns because of which IoT devices remain insecure. This chapter aims to elaborate on the challenges and privacy issues being faced by rapidly growing domestic appliances as well as Industry 4.0 revolution. The main objective is to represent the role of IoT in a day-to-day manner and the current as well as upcoming challenges in this emerging arena.

Privacy preserving Internet of Things: From privacy techniques to a blueprint architecture and efficient implementation

The Internet of Things (IoT) is the internetworking of people and physical devices often called “things” that enable the collection and exchange of data. The number of connections between people and things, as well as the volume of data that is generated by the “things,” is dramatically increasing. In this context, various kinds of data are generated by multiple heterogeneous devices, which operate in different ways and used by different applications with different aims. To realize the distributed execution of IoT systems over multiple resources, different requirements and quality factors must be satisfied. Traditionally, to reduce the effort for developing distributed systems, middleware architectures have been introduced that provide common services such as name and directory services, discovery, data exchange, synchronization, and transaction services, etc. To address the needs and integration of IoT systems, the adoption of middleware seems to be a feasible solution. The Data Distribution Service (DDS) is a middleware that is directly related to data-intensive systems and explicitly considers the quality of service. It is a standard data-centric publish-subscribe programming model and specification for distributed systems that has been applied for the development of high-performance distributed systems such as in the defense, finance, automotive, and simulation domains. In this chapter, we explore and propose the adoption of DDS as a middleware platform for IoT systems. For this, we first describe the requirements for IoT systems and present the IoT reference architecture. Subsequently, we provide a DDS-based architecture for IoT systems based on the Views and Beyond Approach.

Devices are increasingly getting connected to the internet with the advances in technologies called the Internet of Things (IoT). The IoTs are the physical device in which are embedded with software, sensors, among other technologies. Linking and switching data resources with other devices, IoT has been recognized to be a trending research arena due to the world’s technological advancement. Every stage of technology avails several capacities, for instance, the IoT avails any device, anyone, any service, any technological path or any network, any place, and any context to be connected. The effective IoT applications permit public and private business organizations to regulate their assets, optimize the performance of the business, and develop new business models. In this study, we scrutinize the IoT progress as an approach to the technological upgrade through analyzing traits, architectures, applications, enabling technologies, and future challenges. To enable an aging society, and optimize different kinds of mobility and transportation, and helps to enhance the effectiveness of energy, along with the definition and characteristics of the IoT devices, the study examined the architecture of the IoT that includes the perception layer, transmission layer, application layer, and network management. It discusses the enabling technologies of the IoT that include application domain, middleware domain, network domain, and object domain. The study further evaluated the role of the IoT and its application in the everyday lives of the people by making smart cities, smart agriculture and waste management, retail and logistics, and smart environment. Besides the benefits, the IoT has demonstrated future technological challenges and is equally explained within the study.

Internet of Things (IoT) applications can offer a great potential of benefits to end users. We are moving towards an Internet of People, Things and Services (IoPTS) and a future world of ambient intelligence, where users can seamlessly interact with IoT devices and get information about the services they offer. Interaction can take place directly or through dedicated mobile apps that are built to acquire data from sensors or clusters of IoT devices. The article presents a user-centric cluster framework, taking into account the resource-constrained nature of the IoT devices. As part of the framework, the authors propose a Mobility Aware Clustering Scheme (MACS), which organizes the IoT devices in clusters using a fitness function for each node, and a Profile Aware Proactive Cluster Discovery (PAPCD) mechanism using Bluetooth Low Energy (BLE) beacons for service advertisement. The authors also propose an IoT service filtering and ranking algorithm to match the users' preferences and requirements