Internet Of Things Communication Research Articles

A blockchain based federated deep learning model for secured data transmission in healthcare Iot networks

The wide use of sensors in healthcare applications has made it necessary to have secure communication in healthcare Internet of Things (IoT) networks. The sensor data is sensitive, and can contain extremely confidential information such as medical diagnosis, clinical records, vital signs and health data of patients. The emergence of blockchain as a technology ensures consensus and trust among systems, and is now considered to be a new trend used to achieve high scalability, data integrity and privacy. Federated learning is a new technology based on distributed learning that exploits the concept of trust. In federated learning, each user builds an individual distributed model to help a central server that is accessible only to a trusted user group. This paper harnesses the potential of these approaches and proposes an attack detection model to discern normal user behaviours from that of adversaries in an IoT network. This model is called the Blockchain enabled Federated Learning model for secured communication in healthcare IoT (BFL-hIoT), to secure data in healthcare IoT networks. This model is trained and tested on a standard dataset and demonstrates the highest classification accuracy of 97.16 % for normal, 0.9546 for backdoors, 0.9618 for XSS etc., outperforming other blockchain and deep learning models.

An Intrusion Detection System against RPL-based Routing Attacks for IoT Networks

<span lang="EN-US">The significant improvement in the Internet, Internet of Things (IoT), communication, and cloud computing have created considerable challenges in providing security for data and devices. In IoT networks, “Routing Protocol for Low power and Lossy networks”- (RPL) is a communication protocol that enables devices to exchange information and communicate with limited resources like low processing capabilities, less memory and energy. Through the Internet, unauthorised users can access RPL-based IoT networks, making these networks susceptible to routing attacks. Therefore, it is crucial to design Intrusion Detection System-(IDS) to address attacks from IoT communication devices. In this paper, we have proposed GCNConv, a Graph Neural Network (GNN) method that allows capturing the edge and node features of a graph to identify routing attacks. The proposed system has experimented on the RADAR dataset and experimental findings proved that, our approach performs well compared to state-of-the-art method with reference to precision, F1-score, accuracy and recall.</span>

IoT 가상환경 플랫폼에서의 무결성 보장 시스템

In this paper, we propose a system that improves the data integrity of IoT(Internet of Things) devices in the virtual environment by combining Hyperledger Indy and MQTT(Message Queuing Telemetry Transport). The system complements the limitations of the centralized system by realizing a DPKI(Decentralized Public Key Infrastructure) structure that utilizes a distributed network in publish-subscribe(pub/sub) pattern communication. Digital signature technology was applied to ensure the data integrity of IoT devices and communication scenarios between the four core components of the client, IoT device, broker, and blockchain, as well as a topic structure using a decentralized identifier to ensure safety in the virtual environment. We present a systematic method for transparent data exchange. To prove the performance of the proposed system, this paper conducted experiments on four scenarios and evaluated communication performance in a virtual environment. The experimental results confirmed that the proposed system provides a reliable IoT data communication structure in a virtual environment.

Forecasting the probability of successful deployment of internet of things and cloud computing in the building sector through consistent fuzzy preference relations method

Purpose This study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) and cloud computing (CC) in Gujarat, India’s building sector. Design/methodology/approach From the previous studies, 25 significant factors were identified, and a questionnaire survey with personal interviews obtained 120 responses from building experts in Gujarat, India. The questionnaire survey data’s validity, reliability and descriptive statistics were also assessed. Building experts’ opinions are inputted into the CFPR method, and priority weights and ratings for probable outcomes are obtained to forecast success and failure. Findings The findings demonstrate that the most important factors are affordable system and ease of use and battery life and size of sensors, whereas less important ones include poor collaboration between IoT and cloud developer community and building sector and suitable location. The forecasting values demonstrate that the factor suitable location has a high probability of success; however, factors such as loss of jobs and data governance have a high probability of failure. Based on the forecasted values, the probability of success (0.6420) is almost twice that of failure (0.3580). It shows that deploying IoT and CC in the building sector of Gujarat, India, is very much feasible. Originality/value Previous studies analysed IoT and CC factors using different multi-criteria decision-making (MCDM) methods to merely prioritise ranking in the building sector, but forecasting success/failure makes this study unique. This research is generally applicable, and its findings may be utilised for decision-making and deployment of IoT and CC in the building sector anywhere globally.

Future Industrial Applications: Exploring LPWAN-Driven IoT Protocols.

The Internet of Things (IoT) will bring about the next industrial revolution in Industry 4.0. The communication aspect of IoT devices is one of the most critical factors in choosing the device that is suitable for use. Thus far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying strengths and weaknesses. This paper summarizes the network architectures of some of the most popular IoT wireless communications protocols. It also presents a comparative analysis of some of the critical features, including power consumption, coverage, data rate, security, cost, and quality of service (QoS). This comparative study shows that low-power wide area network (LPWAN)-based IoT protocols (LoRa, Sigfox, NB-IoT, LTE-M) are more suitable for future industrial applications because of their energy efficiency, high coverage, and cost efficiency. In addition, the study also presents an Industrial Internet of Things (IIoT) application perspective on the suitability of LPWAN protocols in a particular scenario and addresses some open issues that need to be researched. Thus, this study can assist in deciding the most suitable IoT communication protocol for an industrial and production field.

UAV-Enabled Integrated Sensing, Computing, and Communication for Internet of Things: Joint Resource Allocation and Trajectory Design

UAV-Enabled Integrated Sensing, Computing, and Communication for Internet of Things: Joint Resource Allocation and Trajectory Design

Designing a Secure and Scalable Service Agent for IoT Transmission through Blockchain and MQTT Fusion

With the rapid development of the Internet of Things (IoT) in recent years, many IoT devices use communication systems to transmit data. Data packets are inevitably at risk of tampering during data transmission, which can lead to information errors and damage during communication. Since IoT terminals are often operated under human supervision, it is essential to improve and ensure the transmission of information, avoid data tampering, and ensure the accuracy of packet transmission. This research successfully improves the message transmission method of IoT communication and the communication model by combining it with blockchain architecture. Combining communication protocols with blockchain serial connections eliminates the need to control operating and managing processes. By replacing message transmission with coverage, the reliability of data transmission in the IoT communication system is improved, and the flexibility of the data transmission process is enhanced. Through practical verification through experimentation, the study successfully improved the incapability of effectively constructing a cross-coded message transmission mode in the Message Queuing Telemetry Transport (MQTT) communication protocol, removed a single layer of encryption rule, and created an encryption mode capable of providing complex arrangement organization.

A comprehensive survey on DDoS attacks detection & mitigation in SDN-IoT network

The Internet of Things (IoT) has transformed our lives by introducing new services and enhancing productivity. However, the widespread adoption of IoT devices and communication units has posed challenges in network management. In response, there is a growing necessity to rethink and redesign IoT network control. Software-defined networking (SDN) has emerged as a promising solution, leveraging its programmability and centralized management capabilities. SDN can simplify network management, offer network abstraction, facilitate development, and efficiently handle the complexities of IoT networks. Despite these advantages, security concerns, particularly the threat of Distributed Denial of Service (DDoS) attacks, persist in the IoT landscape. This survey focuses on exploring the collaboration between SDN and IoT. It investigates various types of DDoS attacks and highlights different types of defense, detection, and mitigation methods employed to address DDoS threats in SDN-based IoT (SDN-IoT) networks.

Incorporating the Internet of Things (IoT) Learning Module into the Smart Building Course

The utilization of Internet of Things (IoT) devices is increasing very rapidly, creating a demand for skilled professionals who can navigate the complexities of this technology. It is a crucial educational challenge to prepare undergraduates to become contributors in this emerging field. The curriculum needs to be updated to offer students both theoretical learning and practical application so they can benefit from it. This paper introduces a comprehensive IoT learning module to the final-year students of civil engineering in an elective course, Smart Building. The proposed learning module includes an introduction to IoT concepts and applications, IoT devices, communication protocols, cloud platforms, user interfaces, and IoT risk management and security, all of which can be easily integrated into existing courses. Results from the module are presented using direct and indirect assessments, including assignments, hands-on practical, examinations, and surveys. These assessments are designed to evaluate the students’ understanding and the challenges they encountered in their IoT learning process. The findings indicate that a significant majority, surpassing 90% of the students, have demonstrated understanding of a minimum of three essential components of the fundamental IoT architecture, despite their limited background knowledge at the beginning of the course. Additionally, this learning module can serve as a valuable resource for other educators who intend to deliver IoT-related courses.

Architectural Framework and Feasibility of Internet of Things-Driven Mars Exploration via Satellite Constellations

This study outlines a technical framework for Internet of Things (IoT) communications on Mars, leveraging Long Range (LoRa) technology to connect Martian surface sensors and orbiting satellites. The designed architecture adapts terrestrial satellite constellation models to Martian environments and the specific needs of interplanetary communication with Earth. It incorporates multiple layers, including Martian IoT nodes, satellite linkage, constellation configuration, and Earth communication, emphasizing potential Martian IoT applications. The analysis covers four critical feasibility aspects: the maximum communication range between surface IoT nodes and orbiting satellites, the satellite constellation’s message processing capacity to determine IoT node volume support, the communication frequency and visibility of IoT nodes based on the satellite constellation arrangement, and the interplanetary data transmission capabilities of LoRa-based IoT devices. The findings affirm LoRa’s suitability for Martian IoT communication, demonstrating extensive coverage, sufficient satellite processing capacity for anticipated IoT node volumes, and effective data transmission in challenging interplanetary conditions. This establishes the framework’s viability for advancing Mars exploration and IoT in space exploration contexts.

Energy-Efficient Device-to-Device Communications for Green Internet of Things Using Unmanned Aerial Vehicle-Mounted Intelligent Reflecting Surface

The Internet of Things (IoT) serves as a crucial element in interconnecting diverse devices within the realm of smart technology. However, the energy consumption of IoT technology has become a notable challenge and an area of interest for researchers. With the aim of achieving an IoT with low power consumption, green IoT has been introduced. The use of unmanned aerial vehicles (UAVs) represents a highly innovative approach for creating a sustainable green IoT network. UAVs offer advantages in terms of flexibility, mobility, and cost. Moreover, device-to-device (D2D) communication is essential in emergency communications, due to its ability to support direct communication between devices. The intelligent reflecting surface (IRS) is also a hopeful technology which reconstructs the radio propagation environment and provides a possible solution to reduce co-channel interference resulting from spectrum sharing for D2D communications. The investigation in this paper hence focuses on energy-efficient UAV-IRS-assisted D2D communications for green IoT. In particular, a problem of optimization aimed at maximizing the system’s average energy efficiency (EE) is formulated, firstly, by simultaneously optimizing the power coefficients of all D2D transmitters, the UAV’s trajectory, and the base station (BS)’s active beamforming, along with the IRS’s phase shifts. Second, to address the problem, we develop a multi-agent twin delayed deep deterministic policy gradient (MATD3)-based scheme to find a near-optimal solution, where D2D transmitters, the BS, and the UAV cooperatively learn to improve EE and suppress the interference. To conclude, numerical simulations are conducted to assess the availability of the proposed scheme, and the simulation results demonstrate that the proposed scheme surpasses the baseline approaches in both convergence speed and EE performance.

Secure Device-to-Device Communication in IoT: Fuzzy Identity from Wireless Channel State Information for Identity-Based Encryption

With the rapid development of the Internet of Things (IoT), ensuring secure communication between devices has become a crucial challenge. This paper proposes a novel secure communication solution by extracting wireless channel state information (CSI) features from IoT devices to generate a device identity. Due to the instability of the wireless channel, the CSI features are fuzzy and time-varying; thus, we a employ locally sensitive hashing (LSH) algorithm to ensure the stability of the generated identity in a dynamically changing wireless channel environment. Furthermore, zero-knowledge proofs are utilized to guarantee the authenticity and effectiveness of the generated identity. Finally, the identity generated using the aforementioned approach is integrated into an IBE communication scheme, which involves the fuzzy extraction of channel state information from IoT devices, stable identity extraction for fuzzy IoT devices using LSH, and the use of zero-knowledge proofs to ensure the authenticity of the generated identity. This identity is then employed as the identity information in identity-based encryption (IBE), constructing the device’s public key for achieving confidential communication between devices.

QAKA: A novel quantum authentication and key agreement (QAKA) protocol using quantum entanglement for secure communication among IoT devices

AbstractThe constant evolution of the Internet of Things (IoT) concept involves the idea that all elements in the global network communication are reachable without the need for human intervention. In this context, the paramount concern is security, aiming to safeguard IoT communication against unauthorized access. According to the analysis, the security of the IoT communication framework relies on traditional cryptographic schemes like the RSA algorithm. Nevertheless, the latest developments in quantum computing and information processing pose a significant threat to these established schemes. Motivated by this fact, in this article, we proposed a novel quantum authentication and key agreement (QAKA) protocol that provides unconditional security against any classical and futuristic quantum threats. Our protocol ensures secure key agreement and mutual authentication based on quantum hashing with quantum passwords and quantum key distribution. The proposed scheme utilizes quantum teleportation and Greenberger–Horne–Zeilinger states for secure data transfer among entities. Our work is simulated using the Automated Validation of Internet Security Protocols and Applications tool to prove our protocol's formal correctness and security. The Burrows, Abadi, and Needham logic is applied to prove the goal of our protocol. Random oracle model for formal security analysis is presented in our work. Our protocol is also informally analyzed, considering the characteristics such as correctness, security against repudiation and the impossibility of cloning. The proposed protocol is compared with the related protocols in terms of various security features such as replay attacks, man‐in‐middle attacks and futuristic quantum attacks. Finally, the performance of the proposed protocol is presented, revealing superior efficacy when compared with classical authentication schemes and quantum protocols.

Mobile Handoff with 6LoWPAN Neighbour Discovery Auxiliary Communication

The importance of the topic under investigation stems from the burgeoning prominence of the Internet of Things (IoT) paradigm and the consequent imperative to devise and institute an efficacious methodology for neighbour detection that facilitates supplementary connections to mobile nodes. This research primarily aims to elucidate a mobile handover technique aligning with the neighbour discovery paradigm inherent in 6LoWPAN. The methodological framework employed herein amalgamates a systematic analysis of the foundational tenets governing 6LoWPAN communication standards over the IPv6 protocol in the context of IEEE 802.15.4aa personal wireless networks, supplemented with empirical evaluation of message propagation dynamics among discrete nodes of a designated personal wireless network. The findings of this investigation underscore the pre-eminence of the 6LoWPAN networking standard as a prime vehicle for bolstering the dependable communication of IoT's remote entities, contingent upon the utilization of the IPv6 communication protocol. This iteration of the Internet protocol is superior, particularly in surveillance contexts, given its expansive address capacity (128 bits) juxtaposed against its antecedent, the IPv4 protocol (32 bits). The inherent adaptability of this network connection augments the quality of mobile handover, especially when one considers the real-world application of 6LoWPAN's neighbour discovery auxiliary communication standard. The tangible implications of these findings beckon their potential utility in satiating the demands of IoT system users and actualizing the network collaboration ethos intrinsic to the 6LoWPAN communication standard. 

IOT COMMUNICATION SECURITY: CHALLENGES AND SOLUTIONS

This paper investigates the obstacles and resolutions concerning the security of communicationin the Internet of Things (IoT). It commences with a discussion of the remarkable proliferationof internet-connected devices, ranging from personal computers to mobile devices, and now tothe era of IoT and IoE. The paper illuminates the impact of IoT on network addresses, leading tothe depletion of IPv4 addresses and the necessity for address translation services. Subsequently,the article delves into the risks confronted by IoT systems, encompassing physical and digitalassaults, unauthorized access, system failures, as well as diverse forms of malicious software. Thesignificance of IoT security in industrial and agricultural systems is underscored. Finally, the paperconcludes by presenting strategies to combat these risks, including antivirus countermeasures,safeguards against Distributed Denial-of-Service (DDoS) attacks, and security considerations inIoT systems for agriculture. In essence, this paper offers valuable insights into the challenges andsolutions associated with ensuring the security of IoT communication.

Multi-attribute Feature Fusion Algorithm of IoT Communication Big Data Based on Ant Colony Neural Network

Abstract To address the issues of time-consuming and inaccurate feature fusion in traditional Internet of Things (IoT) communication big data multi-attribute fusion algorithms, a new algorithm based on the ant colony neural network is proposed. Modeling and feature decomposition processing is carried out on IoT communication big data, communication data information and data attribute characteristics are optimized into different data groups according to a data clustering algorithm, and a rough set calculation method is used to calculate information attribute characteristics. The genetic algorithm is used to improve the ant colony neural network, improve the search ability, extract the multi-attribute characteristics of IoT communication big data, filter the current big data’s characteristic attribute demand through the comparison method, and achieve multi-attribute feature fusion of IoT communication big data through the similarity measurement method. The experimental results show that the fusion error of the IoT communication big data multi-attribute feature fusion algorithm based on the ant colony neural network is small and relatively stable. During the 600 MB data fusion process, the data fusion processing time of the method in this paper is 150 ms, and the average energy consumption ratio is below 2 %, which reflects better IoT communication big data multi-attribute feature fusion performance.

Frequency-adjustable OAM antenna with co-divergent beams for IoT applications

A frequency-tunable Orbital Angular Momentum (OAM)-generating antenna array system is introduced for the first time to provide high-data-rate and secure communication for Internet of Things (IoT) infrastructures and devices. Propagation of simultaneous OAM modes brings about the high-data-rate and frequency tunability leads to interference suppression for secure communication. Regarding the design evolution of the proposed structure, the novel Multiple-Input-Multiple-Output (MIMO) antenna consisting of two input ports creates a 2 × 2 UCA, resulting in two 2 × 2 sub-UCA. Feeding each 2 × 2 sub-array with [0°, 90°, 180°, 270°] phase gradients in clockwise and counterclockwise states gives rise to dual-mode OAM-carrying waves with simultaneous excitation capability. It should be mentioned that each MIMO element owns frequency tunability, resulting in a frequency-adjustable dual-mode OAM antenna array. A prototypes of the suggested MIMO antenna as well as the OAM array are fabricated and measured. Changing the applied DC-voltage to the varactor diodes embedded in capacitive stubs of the antenna elements shifts the operating frequency in the MIMO antenna and consequently in the OAM array. Concerning the unique radiation characteristics of the OAM antenna, vortex beams having helical phase fronts are observed, confirming the generation of expected OAM waves. Therefore, it is asserted that the introduced structure, for the first time, proposes new features of frequency-tunability, and co-divergent simultaneous OAM propagation using the MIMO-UCA technique to provide high-data-rate and secure communication in IoT applications.

Technology And Application Outlook of Integrated Circuits Under the Internet of Things

The rapid development of the Internet of Things (IoT) has injected new vitality into the development of integrated circuits (ICs), however, IoT devices have a variety of characteristics that are different from those of traditional electrical equipment, such as complex application environments, small installation space, energy supply difficulties, etc., which also puts forward new requirements for the development of ICs, based on which, this paper presents a certain analysis of the recent innovations in the field of integrated circuits (ICs) in the field of Internet of Things (IoT), which are important for solving the problems of IoT communication, energy supply, circuit design, security and confidentiality, etc. At the same time, the author also puts forward some of his own views on solving related problems. All in all, the article analyzes the problems and possible solutions of ICs in the field of Internet of Things and looks forward to the future development prospects. This is of some significance for the further development of integrated circuits in the field of Internet of Things.

Cryptographic triboelectric random number generator with gentle breezes of an entropy source.

A wind-driven triboelectric nanogenerator (W-TENG) is a promising energy harvesting device due to its clean, ubiquitous and unexhausted properties. In addition, a W-TENG induces unpredictable chaotic outputs from wind flow that can serve as an entropy source for cryptography. This can be applied to a true random number generator (TRNG) for a secured system due to its inherent turbulent nature; thus, a W-TENG with a two-in-one structure can simultaneously generate both power and true random numbers. However, a previously reported W-TENG had one major drawback: a wind velocity of 10m/s is required for stable energy harvesting by wind force. Thus, it is timely to demonstrate a W-TENG-based RNG whose operating condition is below 3m/s, which is a gentle breeze similar to natural wind. In this study, we demonstrate a wind-driven cryptographic triboelectric random number generator (WCT-RNG) by using a W-TENG whose operating condition for wind speed is below 3m/s by adopting a rear-fixed film structure instead of a conventional structure. The rear-fixed film refers to the fluttering film being freestanding on the front-side and fixed on the rear-side, where the front- and rear-sides are the wind inlet and outlet, respectively. The WCT-RNG enables the W-TENG to operate below a 3m/s wind velocity. Because of this, the working time of the WCT-RNG is dramatically enhanced from only 8-42% at an average altitude above sea level. As the capability of operating at low wind speeds is significantly improved, a WCT-RNG becomes more useful and practical for generating both power and true random numbers in a single device. The device can thereby lead to the construction of a self-powered TRNG and secure communication for Internet of Things (IoT) devices in various environments, even under a gentle breeze. In this study, we explain the design of a WCT-RNG structure and also evaluate its randomness by using an NIST SP 800-22 B test suite with a reliability test.

HDS: Heterogeneity-aware dual-interface scheduling for energy-efficient delay-constrained data collection in IoT

With the advancements in low-power and miniature electronics, various smart devices are deployed and interconnected as the Internet of Things (IoT), collecting a massive amount of data from surrounding environments. Despite the popularity of ZigBee for low-power communications in IoT, WiFi has recently been recommended for data collection in IoT for its high data rate, high reliability, native IP compatibility, and vastly-deployed infrastructures. However, it is well known that WiFi is energy-consuming. Although many schemes have been designed to reduce WiFi energy consumption, they usually suffer from the dilemma that a longer (shorter) sleep of WiFi gives a lower (higher) energy consumption but a larger (smaller) latency, hindering the use of WiFi in a wide range of IoT applications that require a certain level of quality of service (QoS). To this end, we propose a Heterogeneity-aware Dual-interface Scheduling (HDS) scheme to fully exploit the heterogeneity between ZigBee and WiFi to realize energy-efficient and delay-constrained data collection in a tree-based IoT network, where each device is equipped with a ZigBee and a WiFi interface. The low-power feature of ZigBee is utilized as much as possible for high energy efficiency, while the high-reliability advantage of WiFi is leveraged when the ZigBee link quality is low for delay guarantee. Under network dynamics, HDS jointly allocates ZigBee and WiFi schedules to strike a balance between energy and delay for optimized performance. A prototype system is built atop an IoT platform integrated with commercial off-the-shelf ZigBee and WiFi modules. Experiment results show that the energy consumption of HDS is 80.3% and 43.6% lower than the standard power saving protocol and a state-of-the-art dual-interface scheme, respectively, under a moderate delay constraint. Additionally, the percentage of data packets that satisfy the delay constraint is above 98.6%.