Internet Of Things Control Research Articles

RBAC-LBRM: An RBAC-Based Load Balancing Assisted Efficient Resource Management Framework for IoT-Edge-Fog Network

The inefficient handling of Internet of Things (IoT) network traffic may result in load-imbalance and unauthorized access, causing network performance degradation. The performance can be improved by off-loading some of the tasks to the network edge and fog layers. The existing works have discussed the issues of load balancing and access control in IoT using edge and fog environments; however, the design of an efficient resource management framework for an IoT-edge-fog environment is still under development. This work presents a role-based access control (RBAC)-based load balancing-assisted efficient resource management framework for IoT-edge-fog network named RBAC-LBRM. The overall average improvements of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">29.85, 16.82, 13.63, and 16.55%</i> have been achieved by RBAC-LBRM over other approaches w.r.t. CPU usage, memory usage, delay, and jitter metrics, respectively.

Sovereign: Self-Contained Smart Home With Data-Centric Network and Security

Recent years have witnessed the rapid deployment of smart homes; most of them are controlled by remote servers in the cloud. Such designs raise security and privacy concerns for end users. In this article, we describe the design of Sovereign, a home Internet of Things (IoT) system framework that provides end users complete control of their home IoT systems. Sovereign lets home IoT devices and applications communicate via application-named data and secures data directly. This approach enables direct, secure, one-to-one, and one-to-many Device-to-Device communication over wireless broadcast media. Sovereign utilizes semantic names to construct usable security solutions. We implement Sovereign as a publish–subscribe-based development platform together with a prototype home IoT controller. Our preliminary evaluation shows that Sovereign provides a systematic, easy-to-use solution to user-controlled, self-contained smart homes running on existing IoT hardware without imposing noticeable overhead.

BEST-Blockchain-Enabled Secure and Trusted Public Emergency Services for Smart Cities Environment.

In the last few years, the Internet of things (IoT) has recently gained attention in developing various smart city applications such as smart healthcare, smart supply chain, smart home, smart grid, etc. The existing literature focuses on the smart healthcare system as a public emergency service (PES) to provide timely treatment to the patient. However, little attention is given to a distributed smart fire brigade system as a PES to protect human life and properties from severe fire damage. The traditional PES are developed on a centralised system, which requires high computation and does not ensure timely service fulfilment. Furthermore, these traditional PESs suffer from a lack of trust, transparency, data integrity, and a single point of failure issue. In this context, this paper proposes a Blockchain-Enabled Secure and Trusted (BEST) framework for PES in the smart city environment. The BEST framework focuses on providing a fire brigade service as a PES to the smart home based on IoT device information to protect it from serious fire damage. Further, we used two edge computing servers, an IoT controller and a service controller. The IoT and service controller are used for local storage and to enhance the data processing speed of PES requests and PES fulfilments, respectively. The IoT controller manages an access control list to keep track of registered IoT gateways and their IoT devices, avoiding misguiding the PES department. The service controller utilised the queue model to handle the PES requests based on the minimum service queue length. Further, various smart contracts are designed on the Hyperledger Fabric platform to automatically call a PES either in the presence or absence of the smart-home owner under uncertain environmental conditions. The performance evaluation of the proposed BEST framework indicates the benefits of utilising the distributed environment and the smart contract logic. The various simulation results are evaluated in terms of service queue length, utilisation, actual arrival time, expected arrival time, number of PES departments, number of PES providers, and end-to-end delay. These simulation results show the effectiveness and feasibility of the BEST framework.

Internet of Things: Development Intelligent Programmable IoT Controller for Emerging Industry Applications.

The Internet of Things (IoT) has become critical to the implementation of Industry 4.0. The successful operation of smart manufacturing depends on the ability to connect everything together. In this research, we applied the TOC (Theory of Constraints) to develop a wireless Wi-Fi intelligent programmable IoT controller that can be connected to and easily control PLCs. By applying the TOC-focused thinking steps to break through their original limitations, the development process guides the user to use the powerful and simple flow language process control syntax to efficiently connect to PLCs and realize the full range of IoT applications. Finally, this research uses oil–water mixer equipment as the target of continuous improvement and verification. The verification results meet the requirements of the default function. The IoT controller developed in this research uses a marine boiler to illustrate the application. The successful development of flow control language by TOC in this research will enable academic research on PLC-derivative applications. The results of this research will help more SMEs to move into smart manufacturing and the new realm of Industry 4.0.

Congestion Control for Internet of Things Based on Priority

Congestion Control for Internet of Things Based on Priority

Automated Hydroponics Notification System Using IOT

This research was conducted to increase the productivity of farmers and to plan the planting of crops by farmers when using a hydroponics system that controls various environmental conditions, in which plant growth factors such as temperature, humidity, water temperature, pH and electrical conductivity are important factors for hydroponics. The Internet of Things control and notifications enabling farmers to quickly modify and improve their crop treatment. This research focuses on use of the Internet of Things to control plant growth factors. Displays and alerts are communicated to the user through a web application where, when comparing plants with controlled growth factors and unregulated systems, it can be seen controlled plant growth factors are in the desired range of the plant, whereas in uncontrolled systems there are unwanted values range of plant, which can cause the plant to not fully grow or even to wither. In this system, farmers are able to view plant growth factor data and can retrospectively view graphs displayed on the web application by this controlled system when the measuring sensors in the system are in range that plants do not want. It prompts farmers to manage the system, which allows them to fix the system quickly and with minimal damage to crops.

Delegated Anonymous Credentials With Revocation Capability for IoT Service Chains (DANCIS)

This article deals with providing privacy-preserving access control in Internet of Things (IoT) systems. Here, a user/IoT device requests access to services provided by other IoT devices and multiple requests are combined to a request-specific service chain. An anonymous delegated credential-based system architecture is proposed, where the requester’s identity is not exposed to the services. The article presents the proposed architecture’s various components including the security aspects. Various options for implementing the architecture on resource-full and resource-constrained services are presented. A prototype of the proposed architecture is then implemented using Linux-based containers to emulate the services. Two representative systems, namely, a small-scale home automation system using a short service chain and a large-scale industrial automation system using a long service chain are considered. Timing measurements from the implementation are presented to demonstrate that the architecture is feasible and can be adapted for practical use in large-scale IoT systems.

Congestion control in Internet of Things: Classification, challenges, and future directions

Internet of Things (IoT) is a collection of billions of smart objects connected via different types of communication media. Although IoT devices generate enormous data, they are still constrained by low processing, power, and limited buffer size. Constraints within smart devices are a prime cause of congestion among IoT networks, causing performance degradation and data loss. Hence, this survey focuses on congestion and related issues as the primary source causing significant performance issues in IoT networks. IoT communication is categorized into reliable and unreliable, identical to the Internet-based systems. This survey presents a detailed study of various congestion control schemes for reliable and unreliable communication, as well as evaluate “divergence” among IoT devices. Congestion control within and among IoT networks is either (i) end-to-end, or (ii) hop-by-hop. We summarize and compare the techniques prevalent among existing IoT networks. We further present a detailed study of communication technologies for IoT devices. Moreover, we focus on the various granularities of congestion for the IoT network stack. We also present essential artifacts in the congestion taxonomy, depicting critical aspects of IoT congestion control. Moreover, we give a detailed study of various congestion control algorithms based on rate adaption and traffic engineering schemes.

Blockchain Based Solutions to Mitigate Distributed Denial of Service (DDoS) Attacks in the Internet of Things (IoT): A Survey.

Internet of Things (IoT) devices are widely used in many industries including smart cities, smart agriculture, smart medical, smart logistics, etc. However, Distributed Denial of Service (DDoS) attacks pose a serious threat to the security of IoT. Attackers can easily exploit the vulnerabilities of IoT devices and control them as part of botnets to launch DDoS attacks. This is because IoT devices are resource-constrained with limited memory and computing resources. As an emerging technology, Blockchain has the potential to solve the security issues in IoT. Therefore, it is important to analyse various Blockchain-based solutions to mitigate DDoS attacks in IoT. In this survey, a detailed survey of various Blockchain-based solutions to mitigate DDoS attacks in IoT is carried out. First, we discuss how the IoT networks are vulnerable to DDoS attacks, its impact over IoT networks and associated services, the use of Blockchain as a potential technology to address DDoS attacks, in addition to challenges of Blockchain implementation in IoT. We then discuss various existing Blockchain-based solutions to mitigate the DDoS attacks in the IoT environment. Then, we classify existing Blockchain-based solutions into four categories i.e., Distributed Architecture-based solutions, Access Management-based solutions, Traffic Control-based solutions and the Ethereum Platform-based solutions. All the solutions are critically evaluated in terms of their working principles, the DDoS defense mechanism (i.e., prevention, detection, reaction), strengths and weaknesses. Finally, we discuss future research directions that can be explored to design and develop better Blockchain-based solutions to mitigate DDoS attacks in IoT.

Decentralized Access Control using Blockchain Technology for Application in Smart Farming

The application of the Internet of Things (IoT) plays a crucial role in the fourth industrial revolution. The sophistication of technology due to the integration of heterogenous smart devices open a new threat from various aspects. Access control is the first line of defence to ensure that IoT resources are secure by preventing illegitimate users from gaining access to these resources. However, access control mechanisms face the limitation of technology in large scale IoT deployments since they are based on a centralized architecture. Significant research concerning decentralized access control solutions for securing IoT resources using combined techniques, such as blockchain, have caught much research attention in recent years. Nevertheless, research for decentralized access control for application in smart farming domain remain as a gap. Thus, this study presented a structured literature review on 81 articles related to the field of access control in IoT and blockchain technology to understand the challenges of centralized access control in securing IoT resources. This study serves as a foundation for decentralized access control using blockchain technology and its application to ensure the IoT actuators and sensors security with the aim to be applied in smart farming. This paper was deliberated based on systematic literature review that was searched from four different database platforms between 2018 and 2021. This study mostly addresses the relevant techniques/approaches including blockchain technology, access control model, key management mechanism and the combination of all three methods. The possible impacts, gap, procedures and evaluation of the decentralized access control are highlighted along with major trends and challenges.

A Traceable Capability-based Access Control for IoT

Delegation mechanism in Internet of Things (IoT) allows users to share some of their permissions with others. Cloud-based delegation solutions require that only the user who has registered in the cloud can be delegated permissions. It is not convenient when a permission is delegated to a large number of temporarily users. Therefore, some works like CapBAC delegate permissions locally in an offline way. However, this is difficult to revoke and modify the offline delegated permissions. In this work, we propose a traceable capability-based access control approach (TCAC) that can revoke and modify permissions by tracking the trajectories of permissions delegation. We define a time capability tree (TCT) that can automatically extract permissions trajectories, and we also design a new capability token to improve the permission verification, revocation and modification efficiency. The experiment results show that TCAC has less token verification and revocation/modification time than those of CapBAC and xDBAuth. TCAC can discover 73.3% unvisited users in the case of delegating and accessing randomly. This provides more information about the permissions delegation relationships, and opens up new possibilities to guarantee the global security in IoT delegation system. To the best of our knowledge, TCAC is the first work to capture the unvisited permissions.

A Robust Framework for MADS Based on DL Techniques on the IoT

Day after day, new types of malware are appearing, renewing, and continuously developing, which makes it difficult to identify and stop them. Some attackers exploit artificial intelligence (AI) to create renewable malware with different signatures that are difficult to detect. Therefore, the performance of the traditional malware detection systems (MDS) and protection mechanisms were weakened so the malware can easily penetrate them. This poses a great risk to security in the internet of things (IoT) environment, which is interconnected and has big and continuous data. Penetrating any of the things in the IoT environment leads to a penetration of the entire IoT network and control different devices on it. Also, the penetration of the IoT environment leads to a violation of users’ privacy, and this may result in many risks, such as obtaining and stealing the user’s credit card information or theft of identity. Therefore, it is necessary to propose a robust framework for a MDS based on DL that has a high ability to detect renewable malware and propose malware Anomaly detection systems (MADS) work as a human mind to solve the problem of security in IoT environments. RoMADS model achieves high results: 99.038% for Accuracy, 99.997% for Detection rate. The experiment results overcome eighteen models of the previous research works related to this field, which proved the effectiveness of RoMADS framework for detecting malware in IoT.

Технология программной имплементации цифрового двойника в контур IoT управления HVAC-системой

The development of application software for cyber-physical systems of buildings involves the widespread use of Internet of Things (IoT) integration platforms. In practice, the flexible functionality of IoT platforms often leads to additional costs for software enhancement of existing and connection of new units, in particular digital twins. The paper proposes a technological solution for the implementation of a digital twin of the ventilation process in the IoT control loop of heating, ventilation and air conditioning (HVAC) systems for buildings and industrial facilities. The implementation and execution of the digital twin in the form of a dynamic simulation model in the object-oriented modelling language Modelica in the OpenModelica environment is considered. The IoT platform InfluxData, based on the TICK stack, is considered as an example of an integration environment. It is a horizontally-oriented IoT platform that contains the mechanism for collecting data from devices and the InfluxDB time-series database for storing metrics. To integrate simulation models on Modelica with InfluxDB, an OMPython server is proposed. In this case, the integration scripts are executed in the Python language, which as a result extends the traditional capabilities of the IoT platform significantly to the level of a digitally twinned control system. This HVAC control involves adapting control loops by taking into account the dynamics of the air distribution process over the ventilation network, evaluating and compensating for process inertia. The publication was prepared within the framework of the Academic Fund Program at the HSE University in 2020–2021 (grant № 21-04-039).

An access control for IoT based on network community perception and social trust against Sybil attacks

SummaryThe evolution of the Internet of things (IoT) has increased the connection of personal devices, mainly taking into account the habits and behavior of their owners. These environments demand access control mechanisms to protect them against intruders, like Sybil attacks, that can compromise data privacy or disrupt the network operation. The social IoT paradigm enables access control systems to aggregate community context and sociability information from devices to enhance robustness and security. This work introduces the ELECTRON mechanism to control access in IoT networks based on social trust between devices to protect the network from Sybil attackers. ELECTRON groups IoT devices into communities by their social similarity and evaluates their social trust, strengthening the reliability between legitimate devices and their resilience against the interaction of Sybil attackers. NS‐3 simulations show the ELECTRON performance under Sybil attacks on several IoT communities so that it has gotten to detect more than 90% of attackers in a scenario with 150 nodes into offices, schools, gyms, and parks communities, and in other scenarios for same communities, it achieved around of 90% of detection. Furthermore, it provided high accuracy, over 90%–95%, and false positive rates closer to zero.

Dynamic-IoTrust: A Dynamic Access Control for IoT Based on Smart Contracts

The Internet of things (IoT) is an active, real-world area in need of more investigation. One of the top weaknesses in security challenges that IoTs face, the centralized access control server, which can be a single point of failure. In this paper, Dynamic-IoTrust, a decentralized access control smart contract based aims to overcome distrusted, dynamic, trust and authentication issues for access control in IoT. It also integrates dynamic trust value to evaluate users based on behavior. In particular, the Dynamic-IoTrust contains multiple Main Smart Contract, one Register Contract, and one Judging Contract to achieve efficient distributed access control management. Dynamic-IoTrust provides both static access rights by allowing predefined access control policies and also provides dynamic access rights by checking the trust value and the behavior of the user. The system also provides to detected user misbehavior and make a decision for user trust value and penalty. There are several levels of trusted users to access the IoTs device. Finally, the case study demonstrates the feasibility of the Dynamic-IoTrust model to offer a dynamic decentralized access control system with trust value attribute to evaluate the internal user used IoTs devices.

Collaborative intrusion detection networks with multi-hop clustering for internet of things

&lt;p&gt;Internet of things (IoT) is an emerging topic in so many aspects nowadays. The integration between devices and human itself is currently in large scale development. With the continuous applications of the IoT, the hidden problems such as security threats become one of the key considerations. Furthermore, limited power and computational capability of the devices in the system make it more challenging.Therefore, the needs of reliable and effective security system throughout the networks are highly needed. This research proposed a collaborative system based on JADE that consists of 3 types of agent, which are IoT server, controller, and node. Every agents will collaborate each other in terms of exchanging the intrusion detection results. The collaboration between the agents will provide more efficient and good performance. Four classification algorithms were used to model IDS functions. Then, the performance evaluation was done on the system with several parameters such as cost loss expectation, energy consumption, and metric of IDS efficiency. The result shows that the number of reports sent by IoT controller were decreased up to 80% while preserving the security aspect.&lt;/p&gt;

Edge and fog computing using IoT for direct load optimization and control with flexibility services for citizen energy communities

The grid congestion and imbalance problems are nowadays approached through a new perspective of the energy flexibility services that are usually acquired through a bidding process by aggregators on behalf of grid operators and electricity retailers and traded via Local Flexibility Markets (LFM). They can be also acquired at a fixed price under specific conditions of interruption and operation. The flexibility services are offered by electricity consumers and prosumers that own generation and storage facilities and controllable appliances, adding value to the emerging Information and Communications Technology (ICT) and smart metering technologies. In this paper, we propose an adaptive direct load optimization and control with an Internet of Things (IoT) architecture and compare it with a classic approach of Direct Load Control (DLC). The optimization process consists in a day-ahead scheduling that aims to minimize the electricity expense using programmable appliances (shift) and their operational constraints, whereas the adaptive DLC comes on top of it with additional load control (shed) using flexibility to cope with real-time uncertainties including the temperature comfort of the consumers. As the consumption is recorded using smart meters and appliances that continuously generate large volumes of data at different time resolution and formats requiring fast analytical and decisional processes, the challenge consists in correlating and integrating the optimization requirements with IoT and appliance control within an edge and fog computing architecture to overcome grid congestion, power capacity scarcity and forecast errors. The simulations are performed using real open datasets consisting in 114 single-family houses that form a small community with modern and flexible appliances, providing that the electricity bill reduction is up to 22.62%. Furthermore, to validate, several indicators for consumers and aggregator are proposed: total daily used flexibility decreased on average by 21.05%, number of interruptions also decreased on average by 20.51%, maximum number of interruptions per appliance decreased by 58.33%, while Peak to Average Ratio (PAR) improved by 32% when implementing the proposed DLC architecture.

Development of Smart Home System based on Mobile Apps Control Using IoT for Educational Purposes

The Internet of Things (IoT) with its enormous growth widens its applications to the living environment of the people by changing a home to a smart home. The smart home is a system, which connect homes with various types of digital devices to communicate with each other through the internet. Based on our prior study, 59% of the respondent among Malaysians are unaware about the IoT or just heard about it without knowing its concept. Thus, this project will present a development of a smart home system based on mobile apps control using IoT to educate Malaysian. This project uses a combination of wireless technology and infrared sensor to detect the motion and a microcontroller to control the usage of appliances in the home. Blynk as a mobile app has been programmed and used to control and display the usage of LED, fan and camera. The output of the appliances will be displayed on the Blynk in kind of LED icon and stream video. The IoT system has been successfully developed and able to follow the instruction given. The LED, fan and camera will turn ON when the switch button in Blynk is pressed. The system has a limited range of operation because it depends on the Wi-Fi signal range, which is about 50 meters of the developed smart home using IoT control. The proposed smart home prototype is useful in the education sector to expose all Malaysian to the current technology especially students and staffs in the university.

Adaptive time-bound access control for internet of things in fog computing architecture

This paper proposes an adaptive Time-Bound Attribute-Based Encryption Scheme (TB-ABE). TB-ABE is a fine-grained data access control scheme that maintains a secure data exchange environment between IoT devices. The lifetime of the system is divided into equal periods of time slots with unique encryption keys. TB-ABE combines Cyphertext-Policy Attribute Based Encryption with Time-bound keys. It only permits data users with attributes that satisfy the access policy set by the data owner to access the data for a specific period. It also proposes an efficient indirect revocation handling mechanism with minimal computations. The proposed scheme is implemented in Fog-Cloud computing architecture, where fog devices are used for partial outsourcing of encryption and decryption operations. This paper provides security and performance analysis for the proposed scheme in terms of computation, storage, communication and energy overheads. Analysis of proposed scheme proves its feasibility for limited-resource devices, while maintaining a secure communication between IoT devices.

Trust-Based Blockchain Authorization for IoT

Authorization or access control limits the actions a user may perform on a computer system, based on predetermined access control policies, thus preventing access by illegitimate actors. Access control for the Internet of Things (IoT) should be tailored to take inherent IoT network scale and device resource constraints into consideration. However, common authorization systems in IoT employ conventional schemes, which suffer from overheads and centralization. Recent research trends suggest that blockchain has the potential to tackle the issues of access control in IoT. However, proposed solutions overlook the importance of building dynamic and flexible access control mechanisms. In this paper, we design a decentralized attribute-based access control mechanism with an auxiliary Trust and Reputation System (TRS) for IoT authorization. Our system progressively quantifies the trust and reputation scores of each node in the network and incorporates the scores into the access control mechanism to achieve dynamic and flexible access control. We design our system to run on a public blockchain, but we separate the storage of sensitive information, such as user’s attributes, to private sidechains for privacy preservation. We implement our solution in a public Rinkeby Ethereum test-network interconnected with a lab-scale testbed. Our evaluations consider various performance metrics to highlight the applicability of our solution for IoT contexts.