Showing papers on "Communications protocol published in 2019"

A Survey of Communication Protocols for Internet of Things and Related Challenges of Fog and Cloud Computing Integration

Abstract: The fast increment in the number of IoT (Internet of Things) devices is accelerating the research on new solutions to make cloud services scalable. In this context, the novel concept of fog computing as well as the combined fog-to-cloud computing paradigm is becoming essential to decentralize the cloud, while bringing the services closer to the end-system. This article surveys e application layer communication protocols to fulfill the IoT communication requirements, and their potential for implementation in fog- and cloud-based IoT systems. To this end, the article first briefly presents potential protocol candidates, including request-reply and publish-subscribe protocols. After that, the article surveys these protocols based on their main characteristics, as well as the main performance issues, including latency, energy consumption, and network throughput. These findings are thereafter used to place the protocols in each segment of the system (IoT, fog, cloud), and thus opens up the discussion on their choice, interoperability, and wider system integration. The survey is expected to be useful to system architects and protocol designers when choosing the communication protocols in an integrated IoT-to-fog-to-cloud system architecture.

ORACLE: Optimized Radio clAssification through Convolutional neuraL nEtworks

Abstract: This paper describes the architecture and performance of ORACLE, an approach for detecting a unique radio from a large pool of bit-similar devices (same hardware, protocol, physical address, MAC ID) using only IQ samples at the physical layer. ORACLE trains a convolutional neural network (CNN) that balances computational time and accuracy, showing 99% classification accuracy for a 16-node USRP X310 SDR testbed and an external database of >100 COTS WiFi devices. Our work makes the following contributions: (i) it studies the hardware-centric features within the transmitter chain that causes IQ sample variations; (ii) for an idealized static channel environment, it proposes a CNN architecture requiring only raw IQ samples accessible at the front-end, without channel estimation or prior knowledge of the communication protocol; (iii) for dynamic channels, it demonstrates a principled method of feedback-driven transmitter-side modifications that uses channel estimation at the receiver to increase differentiability for the CNN classifier. The key innovation here is to intentionally introduce controlled imperfections on the transmitter side through software directives, while minimizing the change in bit error rate. Unlike previous work that imposes constant environmental conditions, ORACLE adopts the ‘train once deploy anywhere’ paradigm with near-perfect device classification accuracy.

High-Reliability and Low-Latency Wireless Communication for Internet of Things: Challenges, Fundamentals, and Enabling Technologies

Abstract: As one of the key enabling technologies of emerging smart societies and industries (i.e., industry 4.0), the Internet of Things (IoT) has evolved significantly in both technologies and applications. It is estimated that more than 25 billion devices will be connected by wireless IoT networks by 2020. In addition to ubiquitous connectivity, many envisioned applications of IoT, such as industrial automation, vehicle-to-everything (V2X) networks, smart grids, and remote surgery, will have stringent transmission latency and reliability requirements, which may not be supported by existing systems. Thus, there is an urgent need for rethinking the entire communication protocol stack for wireless IoT networks. In this tutorial paper, we review the various application scenarios, fundamental performance limits, and potential technical solutions for high-reliability and low-latency (HRLL) wireless IoT networks. We discuss physical, MAC (medium access control), and network layers of wireless IoT networks, which all have significant impacts on latency and reliability. For the physical layer, we discuss the fundamental information-theoretic limits for HRLL communications, and then we also introduce a frame structure and preamble design for HRLL communications. Then practical channel codes with finite block length are reviewed. For the MAC layer, we first discuss optimized spectrum and power resource management schemes and then recently proposed grant-free schemes are discussed. For the network layer, we discuss the optimized network structure (traffic dispersion and network densification), the optimal traffic allocation schemes and network coding schemes to minimize latency.

An Overview of Vehicular Communications

Abstract: The transport sector is commonly subordinate to several issues, such as traffic congestion and accidents. Despite this, in recent years, it is also evolving with regard to cooperation between vehicles. The fundamental objective of this trend is to increase road safety, attempting to anticipate the circumstances of potential danger. Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and Vehicle-to-Everything (V2X) technologies strive to give communication models that can be employed by vehicles in different application contexts. The resulting infrastructure is an ad-hoc mesh network whose nodes are not only vehicles but also all mobile devices equipped with wireless modules. The interaction between the multiple connected entities consists of information exchange through the adoption of suitable communication protocols. The main aim of the review carried out in this paper is to examine and assess the most relevant systems, applications, and communication protocols that will distinguish the future road infrastructures used by vehicles. The results of the investigation reveal the real benefits that technological cooperation can involve in road safety.

Long Range SigFox Communication Protocol Scalability Analysis Under Large-Scale, High-Density Conditions

Abstract: In recent years, the IoT concept is more and more powerful, having set the goal of integrating billions of devices to the Internet. Thus, from this perspective, the interest allocated to low-power wireless networks of sensors is higher than ever. In this paper, the SigFox scalability is analyzed from the IoT concept point of view. In the scientific research, there are a series of papers which tackle the SigFox issues, oftentimes at a comparative study level, without evaluating the performance level of the communication protocol. This paper comes to fill this gap by creating a realistic SigFox communication model. Moreover, a developed and tested generator of SigFox traffic has been implemented, using SDRs. This allows the possibility of evaluating the performance level of WSN networks, of a large-scale high-density-type. Both of the suggested instruments represent the novelty of this paper. The obtained results show that the maximum number of sensors that can transmit data at the same time, using the proposed scenarios, is of approximately 100, in order to obtain a high level of performance when the number of available channels is 360. If we are to increase the number of sensors, an avalanche effect ensues which triggers the sharp decrease of the performance of the SigFox network. At the end of this work, a series of solutions are being suggested with the main purpose of increasing the performance level of large-scale, high-density SigFox networks.

Micro Air Vehicle Link (MAVlink) in a Nutshell: A Survey

Abstract: The micro air vehicle link (MAVLink in short) is a communication protocol for unmanned systems (e.g., drones and robots). It specifies a comprehensive set of messages exchanged between unmanned systems and ground stations. This protocol is used in major autopilot systems, mainly ArduPilot and PX4, and provides powerful features not only for monitoring and controlling unmanned systems missions but also for their integration into the Internet. However, there is no technical survey and/or tutorial in the literature that presents these features or explains how to make use of them. Most of the references are online tutorials and basic technical reports, and none of them presents comprehensive and systematic coverage of the protocol. In this paper, we address this gap, and we propose an overview of the MAVLink protocol, the difference between its versions, and it is potential in enabling Internet connectivity to unmanned systems. We also discuss the security aspects of the MAVLink. To the best of our knowledge, this is the first technical survey and tutorial on the MAVLink protocol, which represents an important reference for unmanned systems users and developers.

Intrusion detection system for automotive Controller Area Network (CAN) bus system: a review

Abstract: The modern vehicles nowadays are managed by networked controllers. Most of the networks were designed with little concern about security which has recently motivated researchers to demonstrate various kinds of attacks against the system. In this paper, we discussed the vulnerabilities of the Controller Area Network (CAN) within in-vehicle communication protocol along with some potential attacks that could be exploited against it. Besides, we present some of the security solutions proposed in the current state of research in order to overcome the attacks. However, the main goal of this paper is to highlight a holistic approach known as intrusion detection system (IDS) which has been a significant tool in securing networks and information systems over the past decades. To the best of our knowledge, there is no recorded literature on a comprehensive overview of IDS implementation specifically in the CAN bus network system. Thus, we proposed an in-depth investigation of IDS found in the literature based on the following aspects: detection approaches, deployment strategies, attacking techniques, and finally technical challenges. In addition, we also categorized the anomaly-based IDS according to these methods, e.g., frequency-based, machine learning-based, statistical-based, and hybrid-based as part of our contributions. Correspondingly, this study will help to accelerate other researchers to pursue IDS research in the CAN bus system.

Physical Layer Security for the Internet of Things: Authentication and Key Generation

Abstract: A low-complexity, yet secure framework is proposed for protecting the IoT and for achieving both authentication and secure communication. In particular, the slight random difference among transceivers is extracted for creating a unique radio frequency fingerprint and for ascertaining the unique user identity. The wireless channel between any two users is a perfect source of randomness and can be exploited as cryptographic keys. This can be applied to the physical layer of the communications protocol stack. This article reviews these protocols and shows how they can be integrated to provide a complete IoT security framework. We conclude by outlining the future challenges in applying these compelling physical layer security techniques to the IoT.

Low-Latency Networking: Where Latency Lurks and How to Tame It

Abstract: While the current generation of mobile and fixed communication networks has been standardized for mobile broadband services, the next generation is driven by the vision of the Internet of Things and mission-critical communication services requiring latency in the order of milliseconds or submilliseconds. However, these new stringent requirements have a large technical impact on the design of all layers of the communication protocol stack. The cross-layer interactions are complex due to the multiple design principles and technologies that contribute to the layers’ design and fundamental performance limitations. We will be able to develop low-latency networks only if we address the problem of these complex interactions from the new point of view of submilliseconds latency. In this paper, we propose a holistic analysis and classification of the main design principles and enabling technologies that will make it possible to deploy low-latency wireless communication networks. We argue that these design principles and enabling technologies must be carefully orchestrated to meet the stringent requirements and to manage the inherent tradeoffs between low latency and traditional performance metrics. We also review currently ongoing standardization activities in prominent standards associations, and discuss open problems for future research.

Secret Sharing-Based Energy-Aware and Multi-Hop Routing Protocol for IoT Based WSNs

Abstract: Internet of Things (IoT) enables modern improvements in smart sensors, RFID, Internet technologies, and communication protocols. Sensor nodes are treated as smart devices and widely used to gather and forward sensed information. However, besides intrinsic constraints on sensor nodes, they are vulnerable to a variety of security threats. This paper presents an energy-aware and secure multi-hop routing (ESMR) protocol by using a secret sharing scheme to increase the performance of energy efficiency with multi-hop data security against malicious actions. The proposed protocol comprises three main aspects. First, the network field is segmented into inner and outer zones based on the node location. Furthermore, in each zone, numerous clusters are generated on the basis of node neighborhood vicinity. Second, the data transmission from cluster heads in each zone towards the sink node is secured using the proposed efficient secret sharing scheme. In the end, the proposed solution evaluates the quantitative analysis of data links to minimize the routing disturbance. The presented work provides a lightweight solution with secure data routing in multi-hop approach for the IoT-based constrained wireless sensor networks (WSNs). The experimental results demonstrate the efficacy of proposed energy-aware and secure multi-hop routing protocol in terms of network lifetime by 38%, network throughput by 34%, energy consumption by 34%, average end-to-end delay by 28%, and routing overhead by 36% in comparison with the existing work.

Interoperability in Smart Manufacturing: Research Challenges

Abstract: Recent advances in manufacturing technology, such as cyber–physical systems, industrial Internet, AI (Artificial Intelligence), and machine learning have driven the evolution of manufacturing architectures into integrated networks of automation devices, services, and enterprises. One of the resulting challenges of this evolution is the increased need for interoperability at different levels of the manufacturing ecosystem. The scope ranges from shop–floor software, devices, and control systems to Internet-based cloud-platforms, providing various services on-demand. Successful implementation of interoperability in smart manufacturing would, thus, result in effective communication and error-prone data-exchange between machines, sensors, actuators, users, systems, and platforms. A significant challenge to this is the architecture and the platforms that are used by machines and software packages. A better understanding of the subject can be achieved by studying industry-specific communication protocols and their respective logical semantics. A review of research conducted in this area is provided in this article to gain perspective on the various dimensions and types of interoperability. This article provides a multi-faceted approach to the research area of interoperability by reviewing key concepts and existing research efforts in the domain, as well as by discussing challenges and solutions.

Edge-AI in LoRa-based Health Monitoring: Fall Detection System with Fog Computing and LSTM Recurrent Neural Networks

Abstract: Remote healthcare monitoring has exponentially grown over the past decade together with the increasing penetration of Internet of Things (IoT) platforms. IoT-based health systems help to improve the quality of healthcare services through real-time data acquisition and processing. However, traditional IoT architectures have some limitations. For instance, they cannot properly function in areas with poor or unstable Internet. Low power wide area network (LPWAN) technologies, including long-range communication protocols such as LoRa, are a potential candidate to overcome the lacking network infrastructure. Nevertheless, LPWANs have limited transmission bandwidth not suitable for high data rate applications such as fall detection systems or electrocardiography monitoring. Therefore, data processing and compression are required at the edge of the network. We propose a system architecture with integrated artificial intelligence that combines Edge and Fog computing, LPWAN technology, IoT and deep learning algorithms to perform health monitoring tasks. In particular, we demonstrate the feasibility and effectiveness of this architecture via a use case of fall detection using recurrent neural networks. We have implemented a fall detection system from the sensor node and Edge gateway to cloud services and end-user applications. The system uses inertial data as input and achieves an average precision of over 90% and an average recall over 95% in fall detection.

Dronemap Planner: A Service-Oriented Cloud-Based Management System for the Internet-of-Drones

Abstract: 1 Low-cost Unmanned Aerial Vehicles (UAVs), also known as drones, are increasingly gaining interest for enabling novel commercial and civil Internet-of-Things (IoT) applications. However, there are still open challenges that restrain their real-world deployment. First, drones typically have limited wireless communication ranges with the ground stations preventing their control over large distances. Second, these low-cost aerial platforms have limited computation and energy resources preventing them from running heavy applications onboard. In this paper, we address this gap and we present Dronemap Planner (DP), a service-oriented cloud-based drone management system that controls, monitors and communicates with drones over the Internet. DP allows seamless communication with the drones over the Internet, which enables their control anywhere and anytime without restriction on distance. In addition, DP provides access to cloud computing resources for drones to offload heavy computations. It virtualizes the access to drones through Web services (SOAP and REST), schedules their missions, and promotes collaboration between drones. DP supports two communication protocols: (i.) the MAVLink protocol, which is a lightweight message marshaling protocol supported by commodities Ardupilot-based drones. (ii.) the ROSLink protocol, which is a communication protocol that we developed to integrate Robot Operating System (ROS)-enabled robots into the IoT. We present several applications and proof-of-concepts that were developed using DP. We demonstrate the effectiveness of DP through a performance evaluation study using a real drone for a real-time tracking application.

IoT and UAV Integration in 5G Hybrid Terrestrial-Satellite Networks.

Abstract: The Fifth Generation of Mobile Communications (5G) will lead to the growth of use cases demanding higher capacity and a enhanced data rate, a lower latency, and a more flexible and scalable network able to offer better user Quality of Experience (QoE). The Internet of Things (IoT) is one of these use cases. It has been spreading in the recent past few years, and it covers a wider range of possible application scenarios, such as smart city, smart factory, and smart agriculture, among many others. However, the limitations of the terrestrial network hinder the deployment of IoT devices and services. Besides, the existence of a plethora of different solutions (short vs. long range, commercialized vs. standardized, etc.), each of them based on different communication protocols and, in some cases, on different access infrastructures, makes the integration among them and with the upcoming 5G infrastructure more difficult. This paper discusses the huge set of IoT solutions available or still under standardization that will need to be integrated in the 5G framework. UAVs and satellites will be proposed as possible solutions to ease this integration, overcoming the limitations of the terrestrial infrastructure, such as the limited covered areas and the densification of the number of IoT devices per square kilometer.

Communication Protocols of an Industrial Internet of Things Environment: A Comparative Study

Abstract: Most industrial and SCADA-like (supervisory control and data acquisition) systems use proprietary communication protocols, and hence interoperability is not fulfilled. However, the MODBUS TCP is an open de facto standard, and is used for some automation and telecontrol systems. It is based on a polling mechanism and follows the synchronous request–response pattern, as opposed to the asynchronous publish–subscribe pattern. In this study, polling-based and event-based protocols are investigated to realize an open and interoperable Industrial Internet of Things (IIoT) environment. Many Internet of Things (IoT) protocols are introduced and compared, and the message queuing telemetry transport (MQTT) is chosen as the event-based, publish–subscribe protocol. The study shows that MODBUS defines an optimized message structure in the application layer, which is dedicated to industrial applications. In addition, it shows that an event-oriented IoT protocol complements the MODBUS TCP but cannot replace it. Therefore, two scenarios are proposed to build the IIoT environment. The first scenario is to consider the MODBUS TCP as an IoT protocol, and build the environment using the MODBUS TCP on a standalone basis. The second scenario is to use MQTT in conjunction with the MODBUS TCP. The first scenario is efficient and complies with most industrial applications where the request–response pattern is needed only. If the publish–subscribe pattern is needed, the MQTT in the second scenario complements the MODBUS TCP and eliminates the need for a gateway; however, MQTT lacks interoperability. To maintain a homogeneous message structure for the entire environment, industrial data are organized using the structure of MODBUS messages, formatted in the UTF-8, and then transferred in the payload of an MQTT publish message. The open and interoperable environment can be used for Internet SCADA, Internet-based monitoring, and industrial control systems.

Security Challenges in Control Network Protocols: A Survey

Abstract: With the ongoing adoption of remotely communicating and interacting control systems harbored by critical infrastructures, the potential attack surface of such systems also increases drastically. Therefore, not only the need for standardized and manufacturer-agnostic control system communication protocols has grown, but also the requirement to protect those control systems’ communication. There have already been numerous security analyses of different control system communication protocols; yet, these have not been combined with each other sufficiently, mainly due to three reasons: First, the life cycles of such protocols are usually much longer than those of other Internet and communication technologies, therefore legacy protocols are often not considered in current security analyses. Second, the usage of certain control system communication protocols is usually restricted to a particular infrastructure domain, which leads to an isolated view on them. Third, with the accelerating pace at which both control system communication protocols and threats against them develop, existing surveys are aging at an increased rate, making their re-investigation a necessity. In this paper, a comprehensive survey on the security of the most important control system communication protocols, namely Modbus, OPC UA, TASE.2, DNP3, IEC 60870-5-101, IEC 60870-5-104, and IEC 61850 is performed. To achieve comparability, a common test methodology based on attacks exploiting well-known control system protocol vulnerabilities is created for all protocols. In addition, the effectiveness of the related security standard IEC 62351 is analyzed by a pre- and post-IEC 62351 comparison.

Deep-Learning-Based Network Intrusion Detection for SCADA Systems

Abstract: Supervisory Control and Data Acquisition (SCADA)networks are widely deployed in modern industrial control systems (ICSs)such as energy-delivery systems. As an increasing number of field devices and computing nodes get interconnected, network-based cyber attacks have become major cyber threats to ICS network infrastructure. Field devices and computing nodes in ICSs are subjected to both conventional network attacks and specialized attacks purposely crafted for SCADA network protocols. In this paper, we propose a deep-learning-based network intrusion detection system for SCADA networks to protect ICSs from both conventional and SCADA specific network-based attacks. Instead of relying on hand-crafted features for individual network packets or flows, our proposed approach employs a convolutional neural network (CNN)to characterize salient temporal patterns of SCADA traffic and identify time windows where network attacks are present. In addition, we design a re-training scheme to handle previously unseen network attack instances, enabling SCADA system operators to extend our neural network models with site-specific network attack traces. Our results using realistic SCADA traffic data sets show that the proposed deep-learning-based approach is well-suited for network intrusion detection in SCADA systems, achieving high detection accuracy and providing the capability to handle newly emerged threats.

Framework of an IoT-based Industrial Data Management for Smart Manufacturing

Abstract: The Internet of Things (IoT) is the global network of interrelated physical devices such as sensors, actuators, smart applications, objects, computing devices, mechanical machines, and people that are becoming an essential part of the internet. In an industrial environment, these devices are the source of data which provide abundant information in manufacturing processes. Nevertheless, the massive, heterogeneous, and time-sensitive nature of the data brings substantial challenges to the real-time collection, processing, and decision making. Therefore, this paper presents a framework of an IoT-based Industrial Data Management System (IDMS) which can manage the huge industrial data, support online monitoring, and control smart manufacturing. The framework contains five basic layers such as physical, network, middleware, database, and application layers to provide a service-oriented architecture for the end users. Experimental results from a smart factory case study demonstrate that the framework can manage the regular data and urgent events generated from various factory devices in the distributed industrial environment through state-of-the-art communication protocols. The collected data is converted into useful information which improves productivity and the prognosis of production lines.

Cooperative Driving and the Tactile Internet

Abstract: The trend toward autonomous driving and the recent advances in vehicular networking led to a number of very successful proposals in cooperative driving Maneuvers can be coordinated among participating vehicles and controlled by means of wireless communications One of the most challenging scenarios or applications in this context is cooperative adaptive cruise control (CACC) or platooning When it comes to realizing safety gaps between the cars of less than 5 m, very strong requirements on the communication system need to be satisfied The underlying distributed control system needs regular updates of sensor information from the other cars in the order of about 10 Hz This leads to message rates in the order of up to 10 kHz for large networks, which, given the possibly unreliable wireless communication and the critical network congestion, is beyond the capabilities of current vehicular networking concepts In this paper, we summarize the concepts of networked control systems and revisit the capabilities of current vehicular networking approaches We then present opportunities of Tactile Internet concepts that integrate interdisciplinary approaches from control theory, mechanical engineering, and communication protocol design This way, it becomes possible to solve the high reliability and latency issues in this context

Effective and efficient network anomaly detection system using machine learning algorithm

Abstract: Network anomaly detection system enables to monitor computer network that behaves differently from the network protocol and it is many implemented in various domains. Yet, the problem arises where different application domains have different defining anomalies in their environment. These make a difficulty to choose the best algorithms that suit and fulfill the requirements of certain domains and it is not straightforward. Additionally, the issue of centralization that cause fatal destruction of network system when powerful malicious code injects in the system. Therefore, in this paper we want to conduct experiment using supervised Machine Learning (ML) for network anomaly detection system that low communication cost and network bandwidth minimized by using UNSW-NB15 dataset to compare their performance in term of their accuracy (effective) and processing time (efficient) for a classifier to build a model. Supervised machine learning taking account the important features by labelling it from the datasets. The best machine learning algorithm for network dataset is AODE with a comparable accuracy is 97.26% and time taken approximately 7 seconds. Also, distributed algorithm solves the issue of centralization with the accuracy and processing time still a considerable compared to a centralized algorithm even though a little drop of the accuracy and a bit longer time needed.

Prototyping post-quantum and hybrid key exchange and authentication in TLS and SSH.

Abstract: Once algorithms for quantum-resistant key exchange and digital signature schemes are selected by standards bodies, adoption of post-quantum cryptography will depend on progress in integrating those algorithms into standards for communication protocols and other parts of the IT infrastructure. In this paper, we explore how two major Internet security protocols, the Transport Layer Security (TLS) and Secure Shell (SSH) protocols, can be adapted to use post-quantum cryptography. First, we examine various design considerations for integrating post-quantum and hybrid key exchange and authentication into communications protocols generally, and in TLS and SSH specifically. These include issues such as how to negotiate the use of multiple algorithms for hybrid cryptography, how to combine multiple keys, and more. Subsequently, we report on several implementations of post-quantum and hybrid key exchange in TLS 1.2, TLS 1.3, and SSHv2. We also report on work to add hybrid authentication in TLS 1.3 and SSHv2. These integrations are in Amazon s2n and forks of OpenSSL and OpenSSH; the latter two rely on the liboqs library from the Open Quantum Safe project.

V2V Routing in a VANET Based on the Autoregressive Integrated Moving Average Model

Abstract: With the development of vehicle networks, the information transmission between vehicles is becoming increasingly important. Many applications, particularly regarding security, are based on communication between vehicles. These applications have strict requirements for factors such as the quality of communication between vehicles and the time delay. Many theoretical communication protocols ignore the presence of buildings or other obstacles that are present during practical use, especially in urban areas. These obstacles can cause a signal to fade or even block direct communication. Many vehicles are often parked at the roadside. Because of their location, these parked vehicles can be used as relays to effectively reduce the shadowing effect caused by obstacles and even solve communication problems. In this paper, we study the problem of parked-vehicle-assistant relay routing communication in vehicle ad hoc networks. We propose an efficient parked vehicle assistant relay routing algorithm that is composed of four parts: a periodic Hello packet exchange mechanism, candidate relay list update, communication link quality evaluation, and candidate relay list selection. Simulation results reveal obvious advantages for indexes such as the quality of communication, success rate, and time delay.

Vehicle-to-Vehicle Communications for Platooning: Safety Analysis

Abstract: Vehicle-to-vehicle (V2V) communication is the key technology enabling platooning. This letter proposes an analytical framework that combines the characteristics of V2V communication (packet loss probabilities and packet transmission delays) with the physical mobility characteristics of vehicles (speed, distance between vehicles and their brake capacities). First, we present the feasible region of communications delays which guarantees safe emergency braking in platooning scenarios. Second, we derive a bound on the probability of safe braking. The presented framework is applied to understand the performance of the state-of-the-art V2V communication protocol for platooning.

Token-Based Security for the Internet of Things With Dynamic Energy-Quality Tradeoff

Abstract: In this paper, token-based security protocols with dynamic energy-security level tradeoff for Internet of Things (IoT) devices are explored. To assure scalability in the mechanism to authenticate devices in large-sized networks, the proposed protocol is based on the OAuth 2.0 framework, and on secrets generated by on-chip physically unclonable functions. This eliminates the need to share the credentials of the protected resource (e.g., server) with all connected devices, thus overcoming the weaknesses of conventional client–server authentication. To reduce the energy consumption associated with secure data transfers, dynamic energy-quality tradeoff is introduced to save energy when lower security level (or, equivalently, quality in the security subsystem) is acceptable. Energy-quality scaling is introduced at several levels of abstraction, from the individual components in the security subsystem to the network protocol level. The analysis on an MICA 2 mote platform shows that the proposed scheme is robust against different types of attacks and reduces the energy consumption of IoT devices by up to 69% for authentication and authorization, and up to 45% during data transfer, compared to a conventional IoT device with fixed key size.

A Survey of Energy-Efficient Communication Protocols with QoS Guarantees in Wireless Multimedia Sensor Networks.

Abstract: In recent years, wireless multimedia sensor networks (WMSNs) have emerged as a prominent technique for delivering multimedia information such as still images and videos. Being under the great spotlight of research communities, however, multimedia delivery over resource- constraint WMSNs poses great challenges, especially in terms of energy efficiency and quality-of-service (QoS) guarantees. In this paper, recent developments in techniques for designing highly energy-efficient and QoS-capable WMSNs are surveyed. We first study the unique characteristics and the relevantly imposed requirements of WMSNs. For each requirement we also summarize their existing solutions. Then we review recent research efforts on energy-efficient and QoS-aware communication protocols, including MAC protocols, with a focus on their prioritization and service differentiation mechanisms and disjoint multipath routing protocols.

An Autonomous Sigfox Wireless Sensor Node for Environmental Monitoring

Abstract: Low-power wide-area network protocols, such as LoRa, Sigfox, and NB Internet of Things, have become a popular technology for long range and limited data communication. Those protocols have been optimized for low power consumption and offer competitive subscription prices. This article presents the development of an autonomous Sigfox sensor node capable of transmitting data collected by a range of sensors directly to the cloud. The device is powered by a solar cell and can transmit data every 5 min under cloudy conditions (<5000 lx). Such a high transmission rate has not yet been reported in the literature for a fully autonomous system. Field trials have been realized by placing two sensor nodes at a vineyard in order to collect meteorological parameters.

Next Generation Lightweight Cryptography for Smart IoT Devices: : Implementation, Challenges and Applications

Abstract: High/ultra-high speed data connections are currently being developed, and by the year 2020, it is expected that the 5th generation networking (5GN) should be much smarter. It would provide great quality of service (QoS) due to low latency, less implementation cost and high efficiency in data processing. These networks could be either a point-to-point (P2P) communication link or a point-to-multipoint (P2M) communication link, which, P2M is also known as multi-casting that addresses multiple subscribers. The P2M systems usually have diverse nodes (also called as ‘Things’) according to services and levels of security required. These nodes need an uninterrupted network inter-connectivity as well as a cloud platform to manage data sharing and storage. However, the Internet of Things (IoT), with real-time applications like in smart cities, wearable gadgets, medical, military, connected driver-less cars, etc., includes massive data processing and transmission. Nevertheless, integrated circuits (ICs) deployed in IoT based infrastructures have strong constraints in terms of size, cost, power consumption and security. Concerning the last aspect, the main challenges identified so far are resilience of the deployed infrastructure, confidentiality, integrity of exchanged data, user privacy and authenticity. Therefore, well secured and effective cryptographic algorithms are needed that cause small hardware footprints, i.e. Lightweight Cryptography (LWC), also with the provision of robustness, long range transfer of encrypted data and acceptable level of security.In this paper, the implementation, challenges and futuristic applications of LWC algorithms for smart IoT devices have been discussed, especially the performance of Long-Range Wide Area Network (LoRaWAN) which is an open standard that defines the communication protocol for Low-Power Wide Area Network (LPWAN) technology.

ECC based inter-device authentication and authorization scheme using MQTT for IoT networks

Abstract: Internet of Things (IoT) has emerged from the proliferation of smart and inter-connected devices ranging from tiny sensors to complex Fog and Cloud nodes, various networking technologies, and communication protocols. These IoT devices permeate in our lives through various applications including smart homes, healthcare, defence, transportation, and so forth. Although IoT provides a way of interaction among the physical world objects and the Internet, these connected devices have created a new dimension of security challenges associated with the vulnerabilities present in them. These challenges can be tackled to some extent by deploying a rigid authentication and access control model. In this paper, we propose a novel light-weight authentication and authorization framework suitable for distributed IoT environment using Elliptical Curve Cryptography (ECC) and Message Queuing Telemetry Transport (MQTT). Moreover, we implement the scheme, and analyse and compare its various security and performance aspects with other schemes.