Management Of IoT Devices Research Articles

Vulnerability Detection in Intelligent Environments Authenticated by the OAuth 2.0 Protocol over HTTP/HTTPS

OAuth 2.0 provides an open secure protocol for authorizing users across the web. However, many modalities of this standard allow these protections to be implemented optionally. Thus, its use does not guarantee security by itself and some of the deployment options in the OAuth 2.0 specification can lead to incorrect settings. FIWARE is an open platform for developing Internet applications of the future. It is the result of the international entity Future Internet Public-Private Partnership. [1,2] FIWARE was designed to provide a broad set of API to stimulate the development of new businesses in the context of the European Union. This platform can be understood as a modular structure to reach a broad spectrum of applications such as IoT, big data, smart device management, security, open data, and virtualization, among others. Regarding security, the exchange of messages between its components is done through the OAuth 2.0 protocol. The objective of the present work is to create a system that allows the detection and analysis of vulnerabilities of OAuth 2.0, executed on HTTP/HTTPS in an on-premise development environment focused on the management of IoT devices and to help developers to implement them ensuring security for these environments. Through the system proposed by this paper, it was possible to find vulnerabilities in FIWARE components in HTTP/HTTPS environments. With this evidence, mitigations were proposed based on the mandatory recommendations by the IETF.

IoT Device Management and Security

IoT Device Management and Security

Unlocking QoS Potential: Integrating IoT services and Monte Carlo Control for heterogeneous IoT device management in gateways

The exponential surge in IoT devices has presented significant challenges in managing network traffic and maintaining Quality of Service (QoS) in IoT networks. To tackle these challenges, ongoing efforts are focused on developing innovative solutions that leverage advanced traffic management techniques, robust QoS mechanisms, and enhanced security protocols. Addressing these obstacles is crucial for the continued growth and success of the IoT system, enabling seamless integration of smart devices and revolutionizing multiple industries and sectors by providing unparalleled connectivity and intelligence. This article proposes an innovative approach to enhance the management of heterogeneous IoT devices and ensure Quality of Service (QoS) in IoT networks. Integrating device categories into the QoS policy aims to optimize overall performance while addressing the diverse QoS requirements of different device categories. The benefits of considering device categories include tailored resource allocation, improved user satisfaction, customized QoS handling, and scalability. The proposed approach utilizes the Monte Carlo Control algorithm to learn an optimal QoS policy through simulations of traffic scenarios. Our paper highlights Monte Carlo Control’s (MCC) rapid learning in diverse IoT settings, peaking at 50 episodes, compared to Q-learning’s 100 episodes and dynamic programming’s 200 episodes. Specifically, in audio IoT, MCC achieved 730 packets/second throughput with a 50 ms delay, outperforming QL (723 packets/second, 134 ms) and DP (700 packets/second, 171 ms). These results underscore MCC’s vital role in elevating IoT Quality of Service, making it pivotal for system performance and user experience optimization.

Leveraging Semantic Technologies for Collaborative Inference of Threatening IoT Dependencies

IoT Device Management (DM) refers to the remote administration of customer devices. In practice, DM is ensured by multiple actors such as operators or device manufacturers, each operating independently via their DM solution. These siloed DM solutions are limited in addressing IoT threats related to device dependencies, such as cascading failures, as these threats spread across devices managed by different DM actors, and their mitigation can no longer be performed without collaborative DM efforts. The first step toward collaborative mitigation of these threats is the identification of threatening dependency topology. However, this task is challenging, requiring the inference of dependencies from the data held by different actors. In this work, we propose a collaborative framework that infers the threatening topology of dependencies by accessing and aggregating data from legacy DM solutions. It combines the assets of Semantic Web standards and Digital Twin technology to capture on-demand the topology of dependencies, and it is designed to be used in business applications such as customer care to enhance customer Quality of Experience. We integrate our solution within the in-use Orange's Digital Twin platform Thing in the future and demonstrate its effectiveness by automatically inferring threatening dependencies in the two settings: a simulated smart home scenario managed by ground-truth DM solutions, such as Orange's implementation of the USP Controller and Samsung's SmartThings Platform , and a realistic smart home called DOMUS testbed.

HIBEChain: A Hierarchical Identity-Based Blockchain System for Large-Scale IoT

Internet-of-Things enables interconnection of billions of devices, which perform autonomous operations and collect various types of data. These things, along with their generated huge amount of data, need to be handled efficiently and securely. Centralized solutions are not desired due to security concerns and scalability issue. In this article, we propose HIBEChain, a hierarchical blockchain system that realizes scalable and accountable management of IoT devices and data. HIBEChain consists of multiple permissioned blockchains that form a hierarchical tree structure. To support the hierarchical structure of HIBEChain, we design a decentralized hierarchical identity-based signature (DHIBS) scheme, which enables IoT devices to use their identities as public keys. Consequently, HIBEChain achieves high scalability through parallel processing as blockchain sharding schemes, and it also implements accountability by use of identity-based keys. Identity-based keys not only make HIBEChain more user-friendly, they also allow private key recovery by validators when necessary. We provide detailed analysis of its security and performance, and implement HIBEChain based on Ethereum source code. Experiment results show that a 6-ary, (7,10)-threshold, 4-level HIBEChain can achieve 32,000 TPS, and it needs only 9 seconds to confirm a transaction.

Access management of IoT devices using access control mechanism and decentralized authentication: A review

Blockchain is a distributed system that enables data transaction security, and its distributed and decentralized design can be used to guarantee safe and scalable IoT device transactions. Since it is essential for resource sharing and data security, access control is a security issue in IoT devices. However, it can be difficult to implement common access control methods in IoT device modes with limited resources. Numerous studies have examined the usage of Blockchain in the Internet of Things to address security problems since the advent of the technology. Traditional AC mechanisms, such as Attribute-based Access Control, Role-based Access Control, and Access Control Lists, are unable to provide a manageable, scalable, and accurate mechanism meeting the needs of IoT systems, effectively protecting the hardware and data in large-scale IoT systems. This study thoroughly examines how blockchain-based decentralized architecture can potentially improve IoT access management.

Practical Use of Secret Sharing for Enhancing Privacy in Clouds

The topic of this contribution is the practical use of secret sharing schemes in securing private data. In the first part, we focus on the security model and the overview of the available solutions. In the second part, we describe our solution for storing sensitive data in commercial cloud storage systems, an application called Datachest. The application uploads the data in encrypted form. Cryptographic keys are divided into shares. Each cloud receives one share. This solution improves the security of users’ sensitive data in the cloud. In the final part, we explore the ramifications of secret sharing on the security and management of IoT devices, especially home appliances.

Attack Detection and Mitigation in MEC-Enabled 5G Networks for AIoT

In recent years, AIoT (Artificial Intelligence of Things) applications have received lots of attention since it exploits widely deployed IoT devices to collect data and perform an action while leveraging AI to obtain knowledge and insights. When deploying AIoT in 5G networks, Multi-access Edge Computing (MEC) is appropriate for enabling local management of IoT devices and computation of machine learning (ML) algorithms. Facing the multitude of threats in the ML data layer, IoT service layer, and 5G communications layer, MEC should enable corresponding detection and mitigation schemes to protect AIoT applications. In this article, we examine the existing security solutions located in each layer and discuss the interrelated challenges. For example, a network-traffic-based IDS solution in MEC might capture IoT malware but fail to identify a growing file-less attack. We suggest that firmware emulation in IoT endpoint should be included to provide system-level behaviors to network-based detectors in MEC so that file-less attacks can be distinguished. The potential of a backdoor attack aiming to poison data or corrupt ML models cannot be ignored in AIoT applications, and a corresponding detector should be implemented in MEC. Due to the rise of low-cost Software-Defined Radio (SDR), malicious attacks using rogue base stations (BSs) have become more popular. It implies that security protection at MEC in the communications layer is necessary. This article, therefore, proposes a novel platform, M3Inspector, where inspectors located in mobiles and AIoT machines collect information from surrounding BSs and provide them to MEC. MEC determines the rogue BS and makes a notification to users subscribing to the local service. A realistic 5G experimental platform with rogue BSs is developed. The results demonstrate that attack detection and mitigation can be implemented in the MEC paradigm to significantly improve the security protection of AIoT from the perspectives of rogue BS attacks and file-less attacks.

Design and Analysis of Intelligent Robot Based on Internet of Things Technology.

This research uses Auto-ID Labs radio frequency identification system to realize the information dissemination from the destination node to the nodes in its neighborhood. The purpose is to forward messages and explore typical applications. Realize the intelligent analysis and management of IoT devices and data. Design a set of edge video CDN system, in the G1 data set A = 9, p = 9, ℤp = 9, lℤp = 8, AES = 5, ES = 9. Distribute some hot content to public wireless hotspots closer to users in advance, A = 9, p = 7, ℤp = 9, lℤp = 9, AES = 9, ES = 8. At present, a large amount of research is mainly to deploy an edge node between the end node of the Internet of Things and the cloud computing center to provide high-quality services. By learning a stable dynamic system from human teaching to ensure the robustness of the controller to spatial disturbances. FPP-SCA plan FPP-SCA = 1.99, FPP-SCA = 1.86, FPP-SCA = 1.03, FPP-SCA = 1.18, FPP-SCA = 1.01, FPP-SCA = 1.46, FPP-SCA = 1.61.The more robots work in an unstructured environment, with different scenarios and tasks, the comparison shows that the FPP-SCA scheme is the optimal model F-S0 = 2.52, F-S5 = 2.38, F-S10 = 2.5, F- S15 = 2.09, F-S20 = 2.54, F-S25 = 2.8, F-S30 = 2.98.

Design and Implementation of a Dynamic IoT Device Management System

Design and Implementation of a Dynamic IoT Device Management System

Blockchain-based IoT device identification and management in 5G smart grid

This work investigates the unified coding and identification of smart grid IoT devices, as more and more IoT devices in smart grid need to be managed and controlled. We combine blockchain technology with 5G MEC to realize the connection of massive power IoT devices at the edge of 5G network. Due to blockchain’s distributed storage and credibility, it is used to identify and register IoT devices in smart grid, ensuring the reliability and accuracy of smart grid IoT devices management. In this paper, we propose a hybrid blockchain mechanism based on 5G MEC smart grid, where both public blockchain and private blockchain are deployed on the MEC gateway/server. To facilitate the data searching and extracting, we endeavor to build a blockchain explorer indexed by IoT device identifier. After that, we study the typical consensus algorithms in the blockchain such as PoW, PoS, DPoS, PDFT, and discuss their feasibility in the hybrid blockchain. Finally, we analyzed and compared the performance of different consensus algorithms from the perspective of average computing time and average time to agreement.

An Efficient Login Authentication System against Multiple Attacks in Mobile Devices

Access management of IoT devices is extremely important, and a secure login authentication scheme can effectively protect users’ privacy. However, traditional authentication schemes are threatened by shoulder-surfing attacks, and biometric-based schemes, such as fingerprint recognition and face recognition, that are commonly used today can also be cracked. Researchers have proposed some schemes for current attacks, but they are limited by usability. For example, the login authentication process requires additional device support. This method solves the problem of attacks, but it is unusable, which limits its application. At present, most authentication schemes for the Internet of Things and mobile platforms either focus on security, thus ignoring availability, or have excellent convenience but insufficient security. This is a symmetry problem worth exploring. Therefore, users need a new type of login authentication scheme that can balance security and usability to protect users’ private data or maintain device security. In this paper, we propose a login authentication scheme named PinWheel, which combines a textual password, a graphical password, and biometrics to prevent both shoulder-surfing attacks and smudge attacks and solves the current schemes’ lack of usability. We implemented PinWheel and evaluated it from the perspective of security and usability. The experiments required 262 days, and 573 subjects participated in our investigation. The evaluation results show that PinWheel can at least effectively resist both mainstream attacks and is superior to most existing schemes in terms of usability.

Blockchain‐Based DNS Root Zone Management Decentralization for Internet of Things

Domain Name System (DNS) is a widely used infrastructure for remote control and batch management of IoT devices. As a critical Internet infrastructure, DNS is structured as a tree‐like hierarchy with single root zone authority at the top, which puts the operation of DNS at risk from single point of failure. The current root zone management is lack of transparency and accountability, since only the root zone file is published as the final outcome of operations inside the root zone authority. Towards distributed root zone operation in DNS, this paper presents a blockchain‐based root operation architecture—RootChain, composed of multiple root servers. On the basis of maintaining the single root authority for top‐level domain (TLD), RootChain decentralizes TLD data publication by empowering delegated TLD authorities to publish authenticated data directly. The transparency and accountability of root zone operation are attained by smart‐contracting the whole life cycle of TLD operation and logging all operations on the chain. RootChain is transparent to recursive/stub resolver and DNS/DNSSEC‐compatible. A proof‐of‐concept prototype of RootChain has been implemented with Hyperledger Fabric and evaluated by experiments.

Communication-Efficient Offloading for Mobile-Edge Computing in 5G Heterogeneous Networks

The unified management of IoT devices with interoperability can be inspired by cloud computing. In addition, sinking the 5G core network to the edge brings chances for the deployment of end-to-end ultralow-latency services. However, the resource efficiency brought by heterogeneous computing devices in 5G spectrum multiplexing environments has encountered challenges. To discuss this issue from a comprehensive perspective, this article first proposes an ultralow-latency service deployment architecture in 5G heterogeneous networks, and three cognitive engines are the key components for efficient service communication across the terminal/edge/cloud computing structure. Then we give an analysis of application task model in the proposed architecture, and following the service response time models are established. In addition, it is efficient to deploy multiuser tasks with constraint resources when the differentiated user requirements are met. Finally, we conducted some experiments and the result statistics are up to our expectations. The first one is the system performance under two microcloud covered cells, and the second one is the performance comparison of the proposed solution with three single scenes of terminal computing, edge computing and cloud computing.

A Scalable Key and Trust Management Solution for IoT Sensors Using SDN and Blockchain Technology

Billions of IoT devices and smart objects are already in operation today and even more are expected to be on the network over time. These IoT devices will generate enormous amounts of data that cannot be allowed to transmit on the network without end-to-end encryption or any trust and security mechanism. Currently, we have certificate authorities that certify the identity of a network device by binding its identity with its public key. However, these certificate authorities are centralized in structure and will not be able to individually certify billions of IoT devices entirely. In this paper, we propose that in an SDN-based IoT network, the identities, i.e., public keys and trust indices of IoT devices, can be stored on a blockchain to ensure immutability and tamper-resistance. The paper presents a novel scalable solution for key and trust management of IoT devices in IoT networks, with a successful proof-of-concept that proves the scalability of the proposed solution. The combination of an IoT network along with blockchain technology and software-defined networking (SDN) is effectively demonstrated through simulation that is able to store the public keys of IoT devices on the blockchain and route the network traffic efficiently through SDN. The performance of the proposed solution is evaluated in terms of throughput and access time delay. The results illustrate that access delay and throughput were not affected linearly or exponentially and the proposed solution shows no significant degradation in the performance with the increase in the number of IoT nodes and packets.

Faulty sensor detection using multi-variate sensors in internet of things (IoTs)

IoT devices are lightweight and have limited computational capabilities often exposed to harsh environments, which can cause failure on the IoT devices [1, 2]. The failure on the IoT devices is also caused due to limited battery life, hardware failure or human mistakes. Sensor faults can be categorized under one type of hardware failure, such as sensor burn, reduced sensor sensitivity and malfunctioned sensors. Any faulty on the IoT devices can cause a problem on the overall operation of the IoT system. Traditional ways in the management of IoT devices is a maintenance officer require to check each device every day [1, 3]. Any faulty devices found needs to be fixed or replaced. This traditional method is not practical and very challenging especially in the management of a large scale deployment of IoT consist of hundreds or thousands devices. Because of this, we proposed a faulty sensor detection and identification mechanism using multivariate sensors. Two methods of decision making are introduced in detecting faulty sensors, which are logical and correlation method that implemented in smart parking system and smart agriculture system accordingly. The logical method compares state of all sensors (ultrasound, IR and hall-effect) in the smart parking system either a parking lot is occupied or available, and then determine the condition of the sensors. The drawback of this method is not able to detect faulty sensor properly for a constant fault, which the sensor reading remains the same value. The correlation method calculates the correlation between all sensors (soil moisture, soil temperature and soil water) in the smart agriculture system. This method uses a moving window technique to calculate the correlation for all sensor over time. Any incomparable and uncorrelated sensor readings means a presence of faulty sensors. Based on the experiment results, the findings shows that the proposed faulty sensor detection mechanism is working properly in detecting faulty sensor in a timely manner.

5G and Wi-Fi 6 Milestones

Papers in the March 2020 issue of the Journal include discussion on the future of the $51 billion National Broadband Network (NBN), IoT device and system management and the mobile cellular networks in Indonesia. The Telecommunications Association is hosting public forums on the future of the NBN in 2020 at RMIT University in Melbourne. The Australian mobile network operators continue to rollout 5G and Telstra has announced a 5G milestone. In the U.S., the FCC has announced the allocation of 1,200 MHz in the 6 GHz band for unlicensed use including Wi-Fi 6. The Journal welcomes contributions on telecommunications and the digital economy.

Development of а software framework for real-time management of intelligent devices

The subject of this paper is development of software framework for real-time management of intelligent devices. The framework enables intelligent management of IoT devices in cyber-physical systems using models based on recurrence relations and differential equations. The platform was developed using Python programming language, Django framework and wide corpus of modules and libraries that supports continuous simulation. The software framework incorporates application programming interface as well, for specification of system behaviour, transmission of input parameters and output results, sending control actions via web services to the IoT system.

Cyber Physical IoT Device Management Using a Lightweight Agent

Cyber Physical IoT Device Management Using a Lightweight Agent

Management of IOT Devices in a Smart Home Through the Application of an Interactive Mirror

Abstract Internet of Things (IoT) devices are big part of concept, which is called by electronic producers and many others Smart Home. Authors of this paper have decided to take a look at it and as a result of this analysis propose and implement (in a form of working prototype) a system that could manage different kinds of devices. The main objective of the project presented in this paper is a device that looks like a mirror and it is known to most people also is an interactive center, a place to obtain information of the devices that surround us and various parameters coming from sensors. Authors have prepared a prototype, that will be the central point of the apartment and will allow users to control all devices connected to this main system. Prototype allows to connect external sensors over GPIO (general purpose input/output) interface or Internet connection. There is also a possibility to add another communication interfaces such as 433MHz radio module, which is very cheap and works great in small areas or bluetooth module.