Internet Of Things Requirements Research Articles

Sliding Window Blockchain Architecture for Internet of Things

Internet of Things (IoT) refers to the concept of enabling Internet connectivity and associated services to nontraditional computers formed by integrating essential computing and communication capability to physical things for everyday usage. Security and privacy are two of the major challenges in IoT. The essential security requirements of IoT cannot be ensured by the existing security frameworks due to the constraints in CPU, memory, and energy resources of the IoT devices. Also, the centralized security architectures are not suitable for IoT because they are subjected to single point of attacks. Defending against targeted attacks on centralized resources is expensive. Therefore, the security architecture for IoT needs to be decentralized and designed to meet the limitations in resources. Blockchain is a decentralized security framework suitable for a variety of applications. However, blockchain in its original form is not suitable for IoT, due to its high-computational complexity and low scalability. In this article, we propose a sliding window blockchain (SWBC) architecture that modifies the traditional blockchain architecture to suit IoT applications. The proposed SWBC uses previous $(n-1)$ blocks to form the next block hash with limited difficulty in proof-of-work (PoW). The performance of SWBC is analyzed on a real-time data stream generated from a smart home testbed. The results show that the proposed blockchain architecture increases security and minimizes memory overhead while consuming fewer resources.

A Comprehensive Method on Fog Computing using Internet-of-Things

The Internet of Things (IoT) characterizes a significant transformation of the way in which our today’s world is expected to interact. IoT is an emerging technology connecting the users towards number of things namely smart phones, smart TV, smart electronic goods like Air Conditioners, and etc. and many smart things. These things involves many processes that has large data, which can be transformed in our daily life .Moreover, it should be analyzed in real-time. These devices collects data and upon processing these data grows exponentially. The Cloud computing provides a space to store the data and it takes long time to deliver to the users. The responses in real time requires very fast access. The Fog Computing accomplishes the solution in getting the greater response especially in the field of Internet of Things. The Fog computing using IoT can be used to sense the environment and work for the requirements. For example connected cars analyzes the surroundings which improves the vehicle maintenance. The fog computing has components like smart devices, sensors and more. Further, Fog computing is the extension of Cloud Computing and it facilitates the applications that uses the cloud computing. This paper presents the methods of fog computing that meets the requirements of IoT that can be used in real-time applications.

Text Data Security and Privacy in the Internet of Things: Threats, Challenges, and Future Directions

In our daily life, Internet-of-Things (IoT) is everywhere and used in many more beneficial functionalities. It is used in our homes, hospitals, fire prevention, and reporting and controlling the environmental changes. Data security is the crucial requirement for IoT since the number of recent technologies in different domains is increasing day by day. Various attempts have been made to cater the user’s demands for more security and privacy. However, a huge risk of security and privacy issues can arise among all those benefits. Digital document security and copyright protection are also important issues in IoT because they are distributed, reproduced, and disclosed with extensive use of communication technologies. The content of books, research papers, newspapers, legal documents, and web pages are based on plain text, and the ownership verification and authentication of such documents are essential. In the current domain of the Internet of Things, limited techniques are available for ownership verification and copyright protection. In the said perspective, this study includes the discussion about the approaches of text watermarking, IoT security challenges, IoT device limitations, and future research directions in the area of text watermarking.

Home Security System with IOT Based Sensors Running On House Infra Structure Platform

In this research a system that is based on IOT technology was developed. The system itself is a subsystem of a home security system. The subsystem is one of the essential parts of a home security system that protects its inhabitants, the house itself and the environment around it. It is based on technology that is related to Internet of Things (IOT). The IOT technology being utilized depends on the data communication infrastructure that is running in a house. The infrastructure is built and based on Lora (long Range) technology and in particular Lorawan. The Infrastructure complies with the demand that it is useful and fulfils the requirements of IOT. Lorawan is quite recent but technically comply with the demands for IOT. This research focused on gas leakage detection using a detector. Gas leakage that needs immediate detection is generally used for home use such as LPG. LPG is generally used in house kitchens or sometimes bath rooms. The developed module is for detection and issuance of warning the existence of LPG in its environment. The data for issuance of warning is communicated to a system called Premises Controller. The protection of a house against gas leakage is essential due to its sensitivity to fire sparks. Fire sparks can trigger fire and often explosion. A sensor’s sensitivity and the time of early warning determine the effectiveness of mitigating efforts.

Image Steganography Based on Artificial Immune in Mobile Edge Computing With Internet of Things

Mobile edge computing provides high computing power, data storage capacity and bandwidth requirements for Internet of Things (IoT) through edge servers that process data close to data sources or users. In practical, mobile edge computing can be used to implement image steganography in IoT. Considering imperceptibility, security and capacity are important indicators for image steganography, this paper propose an image steganography based on evolutionary multi-objective optimization (EMOsteg). The EMOsteg preprocesses the image through a high-pass filters bank to find noise and texture regions that are difficult to model. By perturbing the image on noise and texture regions in multiple directions, the embedded capacity is increased. By defining the imperceptibility and security as an antigen, defining the perturbation positions of the cover image as an antibody, the EMOsteg uses the artificial immune principle to heuristically obtain the perturbation population through feature extraction of the perturbation and adaptive evolution operations. And the Pareto optimal is used to find the optimal perturbation in the last generation population. The simulation experiments analyze the convergence of the algorithm and the diversity of the solutions. In simulation experiments, the MSE, PSNR and SSIM were adopted to evaluate the imperceptibility, and the results show that the MSE value of our algorithm is 0.000308, the PSNR is 82.7501 and the SSIM approaches 1, they are better than comparison algorithms. The average detection error $P_{E}$ under SPA was adopted to detect the security, and the results show that our algorithm is more robust against anti-SPA steganalysis. In order to evaluate the performance of real-time, the embedding time of the same secret under different algorithms were compared, and the results show that our algorithm is faster than comparison algorithms in the terminal. In summary, the proposed algorithm can maintain the image quality while resist steganalysis tools, and realize real-time processing.

An Overview of Continuous Device-to-device Authentication Techniques for the Internet of Things

Internet of things (IoT) has become an integral part of our daily life. However, this technology exposes many security concerns. With the increasing focus on security and privacy, IoT device authentication becomes a crucial requirement to protect devices against any unauthorised access. Although static authentication ensures the legitimacy of the user or device at the beginning of each session, it does not account for session hijacking that could occur after the initial authentication. Continuous authentication is a more robust authentication technique to ensure security throughout the session. Also, it ensures fast authentication for frequent messages sent during the session. In this research, we analyse the security threats in the context of device-to-device communication. We elaborate on the main authentication requirements for IoT. Additionally, we survey major contributions in authentication and compare them based on the predefined requirements. We believe that the findings of this paper provide valuable information to researchers by presenting new directions for future research.

Research on Artificial Intelligence Enhancing Internet of Things Security: A Survey

Through three development routes of authentication, communication, and computing, the Internet of Things (IoT) has become a variety of innovative integrated solutions for specific applications. However, due to the openness, extensiveness and resource constraints of IoT, each layer of the three-tier IoT architecture suffers from a variety of security threats. In this work, we systematically review the particularity and complexity of IoT security protection, and then find that Artificial Intelligence (AI) methods such as Machine Learning (ML) and Deep Learning (DL) can provide new powerful capabilities to meet the security requirements of IoT. We analyze the technical feasibility of AI in solving IoT security problems and summarize a general process of AI solutions for IoT security. For four serious IoT security threats: device authentication, Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks defense, intrusion detection and malware detection, we summarize representative AI solutions and compare the different algorithms and technologies used by various solutions. It should be noted that although AI provides many new capabilities for the security protection of IoT, it also brings new potential challenges and possible negative effects to IoT in terms of data, algorithm and architecture. In the future, how to solve these challenges can serve as potential research directions.

Cooperative Resource Management for Cognitive Satellite-Aerial-Terrestrial Integrated Networks Towards IoT

With the ubiquitous deployment of Internet-of-Things (IoT) devices and applications, satellite-aerial-terrestrial integrated network (SATIN) is regarded as a promising candidate to facilitate global IoT with diverse services. To accommodate the explosive demands of IoT within crowded spectrum, we focus on the cognitive radio based SATINs where spectrum sharing is enabled among satellite, aerial, and terrestrial network segments, and devote to efficient resource management. Specifically, by reviewing main challenges that the characteristics of cognitive SATINs and the requirements of IoT bring to resource management, we analyze the potential of incorporating cooperation into cognitive SATINs for future intelligent IoT. Then, we propose a cooperative beamforming scheme to facilitate secure and energy-efficient IoT communications under limited energy for open channel environments in cognitive SATINs. Simulation results validate the superiority of cooperation resource management in cognitive SATINs towards IoT.

A recursive learning technique for improving information processing through message classification in IoT–cloud storage

Processing and accessing distributed information is a prominent requirement for Internet of Things (IoT) in supporting business and consumer applications to improve accessibility. As the volume of information is being stored and processed is hefty, message classification is challenging in a mobile environment. This also results in prolonged processing delays and backlogs. In order to bridge the gap between message classification and request processing, this paper proposes a classification technique that operates on the basis of request-prioritized recursive learning for ease of message identification and service mapping. This learning technique predicts the type of information and its attributes through intensive learning and services them based on priority to minimize retrieval time. The priority of message servicing relies on the error obtained during the learning process. Despite an increasing number of user requests, attributes associated with each are bundled independently to provide an instant response. Prioritization accounts for the minimum number of error states while learning a message with different attributes to curtail prolonged response time. Error in the learning process is evaluated through a numerical analysis for different learning scenarios of the classified messages. The proposed learning-based access and retrieval technique were analyzed using the metrics of request backlogs, response time, caching delay, and the rate of utilization. The results of experiments verified the effectiveness of the proposed technique in terms of minimizing response time, backlogs, and caching delays, and improving utilization.

A survey on internet of things security: Requirements, challenges, and solutions

Internet of Things (IoT) is one of the most promising technologies that aims to enhance humans’ quality of life (QoL). IoT plays a significant role in several fields such as healthcare, automotive industries, agriculture, education, and many cross-cutting business applications. Addressing and analyzing IoT security issues is crucial because the working mechanisms of IoT applications vary due to the heterogeneity nature of IoT environments. Therefore, discussing the IoT security concerns in addition to available and potential solutions would assist developers and enterprises to find appropriate and timely solutions to tackle specific threats, providing the best possible IoT-based services. This paper provides a comprehensive study on IoT security issues, limitations, requirements, and current and potential solutions. The paper builds upon a taxonomy that taps into the three-layer IoT architecture as a reference to identify security properties and requirements for each layer. The main contribution of this survey is classifying the potential IoT security threat and challenges by an architectural view. From there, IoT security challenges and solutions are further grouped by the layered architecture for readers to get a better understanding on how to address and adopt best practices to avoid the current IoT security threats on each layer.

Pulse mode of operation – A new booster of TEG, improving power up to X2.7 – to better fit IoT requirements

Internet of Things (IoT) is becoming the new driver for semiconductor industry and the largest electronic market ever seen. The number of IoT nodes is already many times larger than the human population and is continuously growing. It is thus mandatory that IoT nodes become self-supplying with energy harvested from environment since periodic exchange of batteries in such a huge number of units (often located in inaccessible places e.g. industrial environment or elements of constructions) is impractical and soon will be simply impossible. Photovoltaic generators may easily harvest energy where light is available, but the IoT nodes often work in dark, hidden locations where the only available energy sources are heat losses. There, ThermoElectric Generators (TEGs) could be the best candidate, if not that if we speak of exploiting heat losses it often means very low temperature differences. This means conditions where TEGs power production drops down dramatically. In this paper we put forward a new idea of TEG's pulse operation that boosts the power production up to X2.7. This extends the domain of applicability of TEGs to lower temperature differences, where conventional TEGs are out of the game. Next, we show that the improvement X2.7 maintains also at larger temperature differences that presents obvious advantages.

LSB: A Lightweight Scalable Blockchain for IoT security and anonymity

In recent years, Blockchain has attracted tremendous attention due to its salient features including auditability, immutability, security, and anonymity. Resulting from these salient features, blockchain has been applied in multiple non-monetary applications including the Internet of Things (IoT). However, blockchain is computationally expensive, has limited scalability and incurs significant bandwidth overheads and delays which are not suited for most IoT applications. In this paper, we propose a Lightweight Scalable blockchain (LSB) that is optimized for IoT requirements while also providing end-to-end security. Our blockchain instantiation achieves decentralization by forming an overlay network where high resource devices jointly manage the blockchain. The overlay is organized as distinct clusters to reduce overheads and the cluster heads are responsible for managing the public blockchain. We propose a Distributed Time-based Consensus algorithm (DTC) which reduces the mining processing overhead and delay. Distributed trust approach is employed by the cluster heads to progressively reduce the processing overhead for verifying new blocks. LSB incorporates a Distributed Throughput Management (DTM) algorithm which ensures that the blockchain throughput does not significantly deviate from the cumulative transaction load in the network. We explore our approach in a smart home setting as a representative example for broader IoT applications. Qualitative arguments demonstrate that our approach is resilient to several security attacks. Extensive simulations show that packet overhead and delay are decreased and blockchain scalability is increased compared to relevant baselines.

Hierarchical resource scheduling method using improved cuckoo search algorithm for internet of things

Current researches for Internet of Things (IoT) QoS mainly focuses on the formulation of service level protocols, which improves some performance of resource scheduling, but there are still many shortcomings in resolving the real-time and personalized requirements of IoT. Aiming at the hierarchical resource scheduling algorithm of the IoT, the key issues of hierarchical resource scheduling are analyzed in detail. The hierarchical resource scheduling of the Internet of Things based on improved heuristic algorithm is deeply studied and explored. A cuckoo search algorithm based on adaptive Cauchy mutation is proposed. Because the algorithm is prone to premature, easy to fall into the local optimal solution, and unable to find the global optimal solution, by introducing mutation operator, the improved algorithm has a certain ability of local random search, while accelerating convergence to the optimal solution in the later period, maintaining the diversity of solutions. The simulation results show that the average service success rate of the proposed resource scheduling algorithm is close to 99%, which can effectively guarantee the relative fairness of user requests, meet the real-time and personalized needs of different users, and improve the utilization rate of resources.

Access control in Internet-of-Things: A survey

The Internet of Things (IoT) is an emerging technology that is revolutionizing the global economy and society. IoT enables a collaborative environment where different entities – devices, people and applications – exchange information for service provision. Despite the benefits that IoT technology brings to individuals, society and industry, its wide adoption opens new security and privacy challenges. Among them, a vital challenge is the protection of devices and resources produced within IoT ecosystems. This need has attracted growing attention from the research community and industry, and several authorization frameworks have been designed specifically for IoT. In this survey, we investigate the main trends in access control in IoT and perform an extensive analysis of existing authorization frameworks tailored to IoT systems. Driven by the needs of representative IoT applications and key requirements for IoT, we elicit the main requirements that authorization frameworks for IoT should satisfy along with criteria for their assessment. These criteria and requirements form a baseline for our literature study. Based on this study, we identify the main open issues in the field of access control for IoT and draw directions for future research.

A semantic-based discovery service for the Internet of Things

With the Internet of Things (IoT), applications should interact with a huge number of devices and retrieve context data produced by those objects, which have to be discovered and selected a priori. Due to the number, heterogeneity, and dynamicity of resources, discovery services are required to consider many selection criteria, e.g., device capabilities, location, context data type, contextual situations, and quality. In this paper, we describe QoDisco, a semantic-based discovery service that addresses this requirement in IoT. QoDisco is composed of a set of repositories storing resource descriptions according to an ontology-based information model and it provides multi-attribute and range querying capabilities. We have evaluated different approaches to reduce the inherent cost of semantic search, namely parallel interactions with multiple repositories and publish-subscribe interactions. This paper also reports the results of some performance experiments on QoDisco with respect to these approaches to handle resource discovery requests in IoT.

Scalable and dynamic replica consistency maintenance for edge-cloud system

With the increasing number of edge devices in the Internet of things (IoT), data storage in edge cloud environment better meet the real-time requirements of IoT. In order to improve the data reliability, reduce the overhead and the response latency, and make more reasonable use of storage resources in edge cloud environment, we conduct an in-depth study on the replica creation strategy and consistency maintenance strategy. In order to reduce the waste of storage resources, a dynamic replica creation strategy based on block popularity and node load (DRC-BN) is proposed. DRC-BN strategy considers the storage cost of edge cloud and the communication cost between central cloud and edge cloud when optimizing the number of replicas, and improves the data reliability. In order to solve the problem of data inconsistency caused by multi-user concurrency, a replica consistency maintenance strategy based on Fast Paxos algorithm (RC-FP) is proposed. RC-FP strategy considers the comprehensive performance of nodes and selects the node with better performance as the leader according to the comprehensive performance of nodes, and reduces the time of consistency maintenance. Experimental results show that the proposed strategies perform well in terms of the consistency maintenance time and the node throughput. At the same time, the proposed strategies also reduce the overall overhead.

Special Issue on Recent Trends and Future of Fog and Edge Computing, Services and Enabling Technologies

Special Issue on Recent Trends and Future of Fog and Edge Computing, Services and Enabling Technologies

Resource and Task Scheduling for SWIPT IoT Systems With Renewable Energy Sources

In this paper, we consider Internet of Things (IoT) systems that can be applied to various applications with low-mobility or static IoT devices, such as wireless sensor networks and charging systems for low-power devices with communication. The IoT systems consist of IoT devices and a hybrid access point (H-AP) powered by both on-grid and renewable energy sources. The IoT devices have a capability to harvest energy from the H-AP’s radio frequency signal, and they perform their tasks by using only their harvested energy. We consider the tasks do not have a real-time requirement which can be stored in the task queues of the IoT devices and performed later. We study resource and task scheduling for the IoT systems which aims at minimizing the on-grid energy consumption at the H-AP while guaranteeing the minimum average data rate and minimum task performing rates of IoT devices. To achieve the goal, we first propose a centralized resource and task scheduling algorithm. However, its computational complexity and signaling overhead are too large due to the task scheduling for each IoT device. Thus, to resolve these issues, we propose a hybrid resource and task scheduling algorithm in which each IoT device determines its own task scheduling in a distributed manner and the H-AP determines the resource scheduling. We then provide performance analyses showing that our proposed algorithms are asymptotically optimal and well satisfy the QoS requirements of IoT devices even with distributed task scheduling. Through the simulation results, we verify the analyses and show the performance of our algorithms.

A survey on low-power wide area networks for IoT applications

We are on the entry of the exponential advancement of the internet-of-things (IoT) due to the quick development of internet-connected smart-objects. As the number of connected smart-objects increase, IoT will continue to advance by providing connectivity and interactions between the physical and the cyber world. This connectivity is characterized by low throughput, delay sensitivity, small and wide coverage, low power consumption, low device, etc. Which explains the emergence of low power wide area network (LPWAN). LPWAN technologies are an alternative promising connectivity solutions for Internet of Things. However, the lack of an overall LPWAN knowledge that present a comprehensive analysis of LPWAN technologies is presently constraining the achievement of the modern IoT vision. In this paper, we begin with a detailed analysis of the conventional high power long-range network technologies that considers IoT applications and requirements. We further point out the need for dedicated low power wide area technologies in IoT systems. In addition, we analyse the technical specification based on the PHY and MAC layers of the technologies that are already deployed, or likely to be deployed. The focus is to incorporate both standard and proprietary technologies in our study. Furthermore, we present the modelling techniques and performance metrics that are adopted in LPWAN networks analysis. Finally, challenges and open problems are presented. The main contribution of this study is that it provides an enhanced summary of the current state-of-the-art of LPWAN suitable to meet the requirements of IoT, while uniquely providing LPWAN’s modelling techniques, performance metrics and their associated enablers.

Trust models of internet of smart things: A survey, open issues, and future directions

Internet of Things (IoT) is a rapidly growing field which provides seamless connectivity to physical objects to make them part of smart environment. In order to fully utilize the potential power of these connected objects of IoT, trust existence among these objects is essential. Traditional security measures are not enough to provide the comprehensive security to this smart world. Trust is used to mitigate the risk of uncertainty while connecting nodes to the internet. Different trust models for IoT environment have been proposed. However, these have not completely mapped with the uncertain and dynamic environment of smart IoT. This paper presents a comprehensive overview of existing surveys on trust models of IoT. It provides classification of Trust Related Attacks (TRA) and comparison of existing trust models with respect to TRA and Function Requirements (FR) of IoT. The aim of this comparison is to summarize the FR of IoT which must be considered while designing Trust Management System (TMS). Furthermore, this survey categorizes and compares existing trust models with respect to their resiliency against TRA, including: attack on node, attack on service, and attack on communication path. The paper expands on current open issues and identifies possible future research directions to address them. Finally, a conceptual framework has been proposed which shows the minimum requirements to make a successful trust model for smart IoT environment. Precisely, this study will help the reader to understand the vulnerabilities in existing IoT trust models and will direct towards future work to propose new models which can cater all possible and highlighted threats.