Internet Of Things Enabled Research Articles

SEGB: Security Enhanced Group Based AKA Protocol for M2M Communication in an IoT Enabled LTE/LTE-A Network

Nowadays machine to machine (M2M) communication and its applications are growing tremendously around the globe as millions of devices are communicating with each other in an Internet of Things (IoT)-enabled long term evolution (LTE)/LTE-advanced (LTE-A) network. These applications are effective and secure only after the successful verification of machine type communication devices (MTCDs). Hence, various group-based authentication and key agreement (AKA) protocols were proposed in the literature to achieve the authentication. These protocols fulfill all the security requirements such as privacy preservation, mutual authentication, integrity, and confidentiality. But, none of them have the credential to overcome the single key problem in the communication network. In addition, they do not have the efficacy to maintain the group key unlink-ability and are susceptible to the identified attacks. In some of the protocols, each MTCD needs to authenticate independently to simultaneously access the communication network that generates network congestion overhead. In view of these problems, we propose the security enhanced groupbased (SEGB) AKA protocol for M2M communication in an IoT-enabled LTE/LTE-A network. The SEGBAKA protocol solves the problem of the single key during the authentication process and achieves the key forward/backward secrecy. The protocol overcomes the problem of signaling congestion and high bandwidth consumption. The formal security analysis of the protocol is carried out by the automated Internet security protocols and applications tool. The security analysis shows that the protocol achieves the security goals and is free from various known attacks. Moreover, the performance of the proposed SEGB-AKA protocol is analyzed with the existing group-based AKA protocols. The analysis shows that the protocol has better results in terms of network overheads and fulfills all the security requirements of M2M communication.

A Survey on 5G Networks for the Internet of Things: Communication Technologies and Challenges

The Internet of Things (IoT) is a promising technology which tends to revolutionize and connect the global world via heterogeneous smart devices through seamless connectivity. The current demand for machine-type communications (MTC) has resulted in a variety of communication technologies with diverse service requirements to achieve the modern IoT vision. More recent cellular standards like long-term evolution (LTE) have been introduced for mobile devices but are not well suited for low-power and low data rate devices such as the IoT devices. To address this, there is a number of emerging IoT standards. Fifth generation (5G) mobile network, in particular, aims to address the limitations of previous cellular standards and be a potential key enabler for future IoT. In this paper, the state-of-the-art of the IoT application requirements along with their associated communication technologies are surveyed. In addition, the third generation partnership project cellular-based low-power wide area solutions to support and enable the new service requirements for Massive to Critical IoT use cases are discussed in detail, including extended coverage global system for mobile communications for the Internet of Things, enhanced machine-type communications, and narrowband-Internet of Things. Furthermore, 5G new radio enhancements for new service requirements and enabling technologies for the IoT are introduced. This paper presents a comprehensive review related to emerging and enabling technologies with main focus on 5G mobile networks that is envisaged to support the exponential traffic growth for enabling the IoT. The challenges and open research directions pertinent to the deployment of massive to critical IoT applications are also presented in coming up with an efficient context-aware congestion control mechanism.

Embedding Machine & Deep Learning for Mitigating Security & Privacy Issues in IoT Enabled Devices & Networks

The future Internet of Things (IoT) will have a deep economical, commercial and social impact on our lives. The participating nodes in IoT networks are usually resource-constrained, which makes them luring targets for cyber-attacks. In this regard, extensive efforts have been made to address the security and privacy issues in IoT networks primarily through traditional cryptographic approaches. However, the unique characteristics of IoT nodes render the existing solutions insufficient to encompass the entire security spectrum of the IoT networks. This is, at least in part, because of the resource constraints, heterogeneity, massive real-time data generated by the IoT devices, and the extensively dynamic behavior of the networks. Therefore, Machine Learning (ML) and Deep Learning (DL) techniques, which are able to provide embedded intelligence in the IoT devices and networks, are leveraged to cope with different security problems. In this paper, we systematically review the security requirements, attack vectors, and the current security solutions for the IoT networks. We then shed light on the gaps in these security solutions that call for ML and DL approaches. We also discuss in detail the existing ML and DL solutions for addressing different security problems in IoT networks. At last, based on the detailed investigation of the existing solutions in the literature, we discuss the future research directions for ML and DL-based IoT security.

IoT Enabled Monitoring of an Optimized Electric Vehicle’s Battery System

The rising number of distributed generation, aging of existing grid infrastructure and appeal for the transformation of networks have sparked the interest in smart grid. For the development and improvement of smart grid, Internet of Things (IoT) technology is an important enabler. Use of Electric Vehicles (EVs) as dynamic electrical energy storage system in smart grid offers numerous advantages while affecting the grid and EV battery pack. To diminish the impact of mass adoption of EVs, this paper proposes an optimization model aimed at maximizing the trade revenue for EV' aggregator for enabling the smart charging. Further, to circumvent the possibility of damage to the EV battery, real-time Battery Monitoring System (BMS) using less complex and easy to implement Enhanced Coulomb Counting Method for SoC estimation and messaging based MQTT as the communication protocol is presented. The proposed BMS is implemented on hardware platform using appropriate sensing technology, central processor, interfacing devices and the Node-RED environment. The Enhanced Coulomb counting method incorporates self-discharge, temperature dependency and degradation due to aging otherwise absent in popular Coulomb counting method.

Mathematical Representation of Quality of Service (QoS) Parameters for Internet of Things (IoT)

Now we are in the era of ubiquitous computing. Internet of things (IoT) is getting matured in various parts of the world. In coming few years' billions and trillions of things will be connected to the internet. To deal with these huge number of devices in a network we need to consider Quality of Service (QoS)parameters so that system operations can be performed in a smoother way. Mathematical modelling of these QoS parameters gives an idea about which factors are needs to consider while designing any IoT-enabled system at the same time it will give the performance analysis of the system before implementation. In this paper comprehensive literature survey is done to discuss various issues related to QoS and gap analysis is also done for IoT Enabled systems. This paper proposes general steps to build a mathematical model for a system. It also proposes the mathematical model for QoS parameters like reliability, communication complexities, latency and aggregation of data for IoT. To support proposed mathematical model proof of concept also given.

Design of an IoT Enabled Local Network Based Home Monitoring System with a Priority Scheme

Internet of things (IoT) is a concept where all devices get connected to the internet to exchange information. IoT can be utilized in order to make a home environment interactive and smart. The required connectivity can be provided by either making all the devices Wi-Fi capable, which is costly, or by setting a local wireless sensor network (WSN) which later connects to internet. In this work various devices and sensors are designed and connected in a wireless sensor network within a home environment which generates a sensor dependent data packet. These data packets are then sent to the cloud through a master node. The master sends the data using a proposed priority scheme so that the critical information can be sent early. Simulations were performed to show that under the proposed scheme the loss of critical sensors information is reduced by around 75%.

Multi-Modal Context-Aware reasoNer (CAN) at the Edge of IoT

Abstract: Future Internet is expected to be driven by prevalence of the Internet of Things (IoT). This prevalence of IoT promises to impact every aspect of human life in the foreseeable future where computing paradigm would witness huge influx of IoT data. Context is gaining growing attention to make sense of the data and it is envisaged that context-aware computing would act as an indispensable enabler for IoT. Contextualizing the collected IoT data enables to reap value from the data and to harvest the knowledge. Reasoning the contextualized data, that is, context information is imperative to the vision of harvesting knowledge. Edge computing is also expected to play a vital role in IoT to reduce dependency on cloud based solution, to achieve faster response, and to provide intelligence closer to the IoT things. The combination of context-awareness and edge solution would be inseparable in the future IoT. Furthermore, IoT vision comprises of different IoT applications controlled by a capable controller at the edge, an edge controller necessitates to counter the challenge of providing knowledge for each of the IoT applications. Therefore, such a controller requires to offer different context-aware reasoning to alleviate the intelligence-of-things. In view of this, this paper proposes a multi-modal context-aware reasoner the aim of which is to provide knowledge at the edge for each IoT application. The context-aware reasoning has been verified with rules-based and Bayesian reasoning for three IoT applications and initial results suggest that it is promising to realize such multimodal reasoning at the edge with low latency.

IoT Enabled Low Cost Wearable Device for Location and Information Tracking System

An internet-of-things (IoT) enabled low cost wearable device for location and information tracking system is developed to monitor and ensure the safety of the children while their parents are away either to work or abroad. This system aims to ensure human safety especially the children and efficiently initiate search and rescue in the event of emergencies. The device will notify the parents on the condition of the surroundings of the children, specifically inside the house and notify the parents if the children are outside the target area by using the application developed in the smartphone. The system uses a microcomputer called Beagle-Bone Black (BBB) as the processor while GPS and LTE technology for wireless communication. Future improvement mainly focuses on reducing the size and power consumption of the device, improving communication module, and optimizing microcomputer’s specification.

A Strenous Macroanalysis on the Substratals of Securing Bluetooth Mobile Workforce Devices

Objectives: Bluetooth is extending to the blooming Internet of Things (IoT). This article provides an extensive literature survey on the security mechanisms; operational range of Bluetooth. Statistical Analysis: The user can achieve 3 Mbps data rate across an operational range of 100 meters. Bluetooth is a pretty impressive technology that connects and controls all the devices over a distance by using an IoT enabled APP due to which is there is a high possibility of Bluetooth charging for its services like the Internet Service Provider (ISP). Bluetooth 4.0 features reliable pairing and encryption whereas the earlier versions had less importance on security. Findings: In spite of the inherent security in Bluetooth, insidious security issues remain around Bluetooth transfer. Most of the problems were identified and rectified but still as the usage and technology improves, undiscovered problems bloom. There is no software in Bluetooth that has zero security vulnerabilities. Security threats can be overcome by generating a random key. This key is generated in random by combining the significant features of the device along with the customized features of the person. Improvements: Security can be upgraded by improving the strength of Authentication; Encryption algorithm; Augmenting Range of Bluetooth by making it IoT Enabled.

Forensic investigation of P2P cloud storage services and backbone for IoT networks: BitTorrent Sync as a case study

Cloud computing can be generally regarded as the technology enabler for Internet of Things (IoT). To ensure the most effective collection of evidence from cloud-enabled IoT infrastructure, it is vital for forensic practitioners to possess a contemporary understanding of the artefacts from different cloud services and applications. In this paper, we seek to determine the data remnants from the use of the newer BitTorrent Sync applications (version 2.x). Findings from our research using mobile and computer devices running Windows, Mac OS, Ubuntu, iOS, and Android devices suggested that artefacts relating to the installation, uninstallation, log-in, log-off, and file synchronisation could be recovered, which are potential sources of IoT forensics. We also extend the cloud forensics framework of Martini and Choo to provide a forensically sound investigation methodology for the newer BitTorrent Sync applications.

Breathe to Save Energy: Assigning Downlink Transmit Power and Resource Blocks to LTE Enabled IoT Networks

Undoubtedly, the Internet of Things (IoT) is the next big revolution in the field of wireless communication networks. IoT is an invisible network, which connects the physical world to the virtual world. Seamless Internet connectivity is essential between these two worlds for IoT to become a reality. In this aspect, long-term evolution advanced (LTE-A) is a promising technology, which meets the requirements of IoT. However, an exponential increase in the number of IoT devices will increase the energy consumption at base stations in LTE-A. Therefore, in this letter, we study the downlink energy efficiency aspect of LTE-A in the IoT networks. We propose a power control and resource block allocation scheme called breathing for an IoT network. Simulation results have shown that breathing performs better than the traditional maximum power allocation scheme and greedy power reduction scheme in terms of energy efficiency, system throughput, and system blocking.

Customized IoT Enabled Wireless Sensing and Monitoring Platform for Smart Buildings

In this paper we present a customized Internet of Things (IoT) enabled Wireless Sensing and Monitoring Platform to monitor the temperature, relative humidity and light in the context of building automation. In developed system, data is sent from the transmitter node to the receiver node through a customized hopping method. The data received at the receiver node is monitored and recorded in an excel sheet in a personal computer (PC) through a Graphical User Interface (GUI), made in LabVIEW. An Android application has also been developed through which data is transferred from LabVIEW to a smartphone through which data is remotely monitored.

IoT Enabled Analysis of Irrigation Rosters in the Indus Basin Irrigation System

The Indus Basin Irrigation System (IBIS) is the world's largest contiguous irrigation system, irrigating over 2.5 million acres and running over 90,000 km of watercourses. It ensures equitable water distribution to farmers through irrigation rosters or warabandi (literally meaning “taking turns”) which is a fixed-turn rotation system following a time roster issued by the government agencies. To study this irrigation system, we have developed an Internet-of-Things (IoT) inspired custom-built water metering network, capable of near real-time reporting of flow discharges through GPRS and backend server services. In 2013-14, a network of flow meters was deployed on 17 distributary canals in the Hakra Branch Canal command in IBIS covering more than two cropping seasons. By comparing the captured water distribution data (sampled every 10 minutes) with Punjab Irrigation Department (PID) issued warabandi rosters, an analysis of the warabandi rosters is presented in this paper.

Efficient P2P-based mutual authentication protocol for RFID system security of EPC network using asymmetric encryption algorithm

Internet of Things (IoT) is a new vision of the future technological ubiquity in ubiquitous computing, which becomes the mapping from the real world to the digital one. Radio frequency identification (RFID) technology is a key enabler of the future IoT and it has a great economical potential. However, the RFID system uses of Electronic Product Code (EPC) tags can drastically threaten the security of applications. With the widespread use of RFID technology, its security problems become the hot topic in the academic and industrial fields. Aiming at the RFID network's security problems, we propose a novel P2P based RFID network architecture (P2P-RFID), and analyze the security problems in this kind of network. And a feasible and scalable protocol to guarantee P2P-RFID network security is also presented in this paper. The proposed protocol uses P2P storage technology together with the utilizing of asymmetric encryption algorithm (RSA) based authentication. An analysis proves that the presented protocol is secure. Moreover, the protocol authentication does not require a Certificate Authentication (CA) database, which avoids the single-point bottleneck.