Scheme For Internet Of Things Research Articles

Security and Privacy Analysis of Vinoth et al.’s Authenticated Key Agreement Scheme for Industrial IoT

Vinoth et al. proposed an authenticated key agreement scheme for industrial IoT (Internet of Things) applications. Vinoth et al.’s scheme aimed to protect the remote sensing data of industrial IoT devices under hostile environments. The scheme is interesting because the authorized user is allowed simultaneously to access the multiple IoT sensing devices. Therefore, we carefully analyzed the security and privacy implications of Vinoth et al.’s scheme. Our findings are summarized as follows. One, Vinoth et al.’s scheme failed to defeat user impersonation attacks. Second, Vinoth et al.’s scheme did not prevent IoT sensing device impersonation attacks. Third, Vinoth et al.’s scheme suffered from replay attacks. Fourth, Vinoth et al.’s scheme was vulnerable to desynchronization attacks. Fifth, Vinoth et al.’s scheme could not maintain user privacy. As a case study, our analysis results enlighten researchers and engineers on the design of robust and efficient authenticated key agreement schemes for IoT applications.

Non-Interactive and Secure Data Aggregation Scheme for Internet of Things

The popularity of mobile devices in Internet of Things has brought great convenience to the lives of the people. Massive data generated in the IoT are outsourced and stored on cloud platforms so that data aggregation and analysis can be performed on the massive data. However, these data often contain sensitive information of mobile devices, so effective protection of mobile user privacy is the primary condition for further development of IoT. Most of the current data aggregation schemes require a lot of interactions between users, and thus this paper designs a non-interactive secure multidimensional data aggregation scheme. This scheme adopts an additive secret sharing technique to mask the shared data and send it to two non-colluding servers, and then the servers aggregate the ciphertext respectively. Different from the existing schemes, our proposed scheme achieves non-interaction between users, and the aggregation result is kept confidential to the server and supports mobile users offline. Finally, we perform an experimental evaluation which proves the effectiveness of our scheme.

A secure and efficient certificateless signature scheme for Internet of Things

The Internet of Things (IoT) is a new technological innovation, which makes things intelligent and our life more convenient. To ensure secure communication between smart objects in the IoT, certificateless signature is a feasible cryptographic tool to provide data integrity and identity authentication, which eliminates the cumbersome certificate management in the certificate-based signature system, as well as the key escrow problem in the identity-based cryptosystem. However, most of the existing certificateless signature schemes are not all secure to resist various attacks, such as public key replacement attacks or malicious-but-passive key-generation-center attacks. Besides, due to the limited storage and processing capabilities of these smart things, they are unable to meet the real-time demands of the IoT completely. This paper first analyzes Jia’s scheme. We prove that the claimed solution is not resistant to the Type II strong adversaries. Then, we propose a novel certificateless signature scheme and prove its existentially unforgeable under the elliptic curve discrete logarithm problem assumption. Finally, the comprehensive performance evaluations indicate that, at the same security level, our scheme is more efficient than other certificateless signature schemes and is well suitable for the resource-constrained IoT environment.

The Framework of 6G Self-Evolving Networks and the Decision-Making Scheme for Massive IoT

The increasingly huge amount of device connections will transform the Internet of Things (IoT) into the massive IoT. The use cases of massive IoT consist of the smart city, digital agriculture, smart traffic, etc., in which the service requirements are different and even constantly changing. To fulfill the different requirements, the networks must be able to automatically adjust the network configuration, architectures, resource allocations, and other network parameters according to the different scenarios to match the different service requirements in massive IoT, which are beyond the abilities of the fifth generation (5G) networks. Moreover, the sixth generation (6G) networks are expected to have endogenous intelligence, which can well support the massive IoT application scenarios. In this paper, we first propose the framework of the 6G self-evolving networks, in which the autonomous decision-making is one of the vital parts. Then, we introduce the autonomous decision-making methods and analyze the characteristics of the different methods and mechanisms for 6G networks. To prove the effectiveness of the proposed framework, we consider one of the typical scenarios of massive IoT and propose an artificial intelligence (AI)-based distributed decision-making algorithm to solve the problem of the offloading policy and the network resource allocation. Simulation results show that the proposed decision-making algorithm with the self-evolving networks can improve the quality of experience (QoE) compared with the lower training.

An Efficient Information Aggregation Scheme in Internet of Things: Multi Agent based Approach

The use of wireless sensor technology in various Internet of Things (IoT) applications is growing rapidly. With the exponential increase of smart devices and their applications, collecting and analyzing data is gradually becoming one of the most difficult tasks. As sensor nodes are powered by batteries, energy efficiency is essential. To that intention, before passing the final data to the central station, a sensor node should reduce redundancies in the received data from neighbor nodes. There will be some redundancy in the data because different sensor nodes typically notice the same phenomenon. Data aggregation is one of the most important approaches for eliminating data redundancy and improving energy efficiency, as well as extending the life time of wireless sensor networks. Furthermore, the effective data aggregation technique might help to reduce network traffic. In this paper we have proposed cluster based data aggregation using intelligent agents. The performance of the proposed scheme is compared with Centralized Data Aggregation (CDA) mechanism in IoT.

A secure and lightweight certificateless hybrid signcryption scheme for Internet of Things

The encryption and signature schemes based on traditional public key are no longer applicable for devices with limited hardware and software resources in the Internet of Things (IoT), since those schemes consume too much hardware and software. To ensure the security and efficiency of data transmission, we construct a secure and lightweight certificateless hybrid signcryption scheme for IoT. Compared with the existing schemes, this scheme only needs one bilinear calculation for one communication, which is computationally efficient for protecting the secure communication between nodes with limited resources in IoT. To meet the security requirements of the complex IoT, based on the difficult problem assumption of bilinear pairings, this scheme can simultaneously meet security requirements of the IoT such as confidentiality, unforgability, semipublic verification, forward security and known session-specific temporary information security. In addition, we prove the security and correctness of this scheme in Random Oracle Model (ROM).

An Affordable, Scalable, Open Architecture, IoT Eco-system for the Academic Community

Aim: Today, Internet of Things (IoT) applications are extended from smart homes to ehealth, cyber security, data analytics, logistics and management of assets. There are many upcoming IOT solutions and platforms like ThingWorx, Xively, and Yaler. However, the existing eco-systems are not vibrant because of the high entry-level barrier and low potential for any stakeholder. Especially, the academic community requires a comprehensible way to create IoT services, develop their skillsets and build applications around them. In this regard, this work presents an affordable and scalable IoT eco-system with an easily programmable hardware platform, a private web server on the cloud and a user-friendly mobile application. Background: Home automation controls the devices and appliances in the home environment to increase the comfort and convenience. To design a typical immune home automation system, we need to incorporate different sensors, wireless networking and a central node that can collect data and act as a gateway for the internet connection. Objective: Delivering an IoT solution involves the use of multiple technologies that cut across traditional engineering stream boundaries - sensors, microcontrollers, wireless networking, network protocols, web programming, and mobile app development. The open challenge is to put the entire ecosystem together either through new development or through configuartion of existing components. Methods: In this work, we incorporated a suitable hardware platform that can be easily programmed. The platform is open so that new sensors and actuators can be added as per requirement. The existing web services are used to post and retrieve data from the cloud. In addition, mobile apps can be developed to make data available to the user. Results: A custom-built GISMO based IoT cloud system is developed with sensors and nodes to form an infrastructure. The framework will assure standard design that establishes a functional link between hardware, software and web applications. A private web service using HTTP server and MQTT broker is designed with access from anywhere with a public IP. The web services are coded in PHP and since it is an in-house development, the addition of new services and maintenance of existing services are easy. Conclusion: The IoT eco-system developed provides a platform for a quick out-of-the-box implementation of an IoT project. Other sensors such as a PIR sensor, an RTC module, an ultrasonic sensor, a soil moisture sensor have been interfaced to the GISMO module using the IOs brought out onto the expansion header. The GISMO thus can serve as a generic hardware platform for sensor/actuator interface in the IoT scheme. The eco-system can be replicated in other institutes and can serve as a base to implement applications like sensor-to-cloud interface, cloud-to-actuator interface, cloud-based alerts and notifications, HTTP and MQTT protocols usage.

Energy Efficient Data Gathering in IoT Networks With Heterogeneous Traffic for Remote Area Surveillance Applications: A Cross Layer Approach

In this paper, the problem of energy-efficient data gathering in an Internet of Things (IoT) based remote area surveillance application is addressed by designing a suitable MAC layer uplink solution. We follow the 3GPP specified scheduled access scheme for narrowband IoT (NB-IoT) and consider presence of both delay sensitive and delay tolerant traffic in the network. First, we present a mixed integer non-linear programming (MINLP) based optimization framework to minimize the IoT devices’ cumulative transmission energy per uplink frame under the constraints of finite resource blocks, mean queue stability and residual energy levels of IoT nodes. A cross layer approach has been adopted. Precisely, using Lyapunov optimization, we propose a dynamic, distributed transmit power allocation for IoT nodes and a centralized node scheduling scheme. Further, assuming Poisson model for traffic generation at delay tolerant traffic generating nodes, we suggest a distributed probabilistic sleep scheduling scheme to improve the average delay experience of delay sensitive traffic while improving the overall energy conservation. Simulation results suggest impressive performance of our proposed solution over the existing uplink solution for NB-IoT, in terms of delay experience of delay sensitive traffic, buffer length requirement and nodes’ total energy consumption at high traffic load.

Compressive sensing based routing and data reconstruction scheme for IoT based WSNs

Data acquisition problem on large distributed wireless sensor networks (WSNs) is considered as a challenge in the growth of Internet of Things (IoT). Recently, the combination of compressive sensing (CS) and routing techniques has attracted much attention of researchers. An open question of this combination is how to integrate these techniques effectively for specific tasks. On the other hand, CS data reconstruction process is considered as one of the CS challenges because it requires to recover N data from only M measurement where M< <N. Through this paper, we propose a new scheme for data gathering in IoT based heterogeneous WSN that includes a new effective Deterministic Clustering using CS technique (DCCS) to handle the data acquisition problem. DCCS reduces the total overhead computational cost needed to self-organize WSN using a simple approach and then uses CS at each sensor node to decrease the overall energy consumption and increase the network lifetime. The proposed scheme includes also an effective CS reconstruction algorithm called Random Selection Matching Pursuit (RSMP) to improve the recovery process at the base station (BS). RSMP adds a random selection process during the forward step to give the opportunity for more columns to be selected as an estimated solution in each iteration. The simulation results show that the proposed scheme succeeds to minimize the overall network power consumption and prolong the network lifetime beside provide better performance in CS data reconstruction.

A PUF-based secure wake-up scheme for Internet of Things

Internet of Things (IoT) are typically powered by limited-capacity batteries. Thus, reducing energy consumption is a critical issue for the success of IoT. Recently, Wake-up Radios (WuRs) play a key role in minimizing the energy consumption by providing wake-up calls to IoT devices which are currently in a low-power sleep mode to conserve energy. On receiving a pre-defined pattern called a Wake-up Token (WuT) over the WuR, the IoT device wakes up in order to process information and/or conduct communications. However, WuR-based IoT devices are susceptible to malicious attacks, such as Denial-of-Sleep attacks designed to drain the device of its energy, or cloning attacks designed to impersonate a legitimate IoT device and perform various nefarious activities. To address these problems, the present study proposes a novel one-time wake-up token using the Physical Unclonable Function (PUF). In addition, to prevent the WuT from becoming desynchronized thereby resulting in a connection loss, a WuT resynchronization scheme is designed to maintain a constant state of synchronization between the WuTs of the gateway and the IoT devices, respectively. Finally, the proposed schemes are extended to support group wake-up and resynchronization procedures, respectively, in order to enhance the communication efficiency and improve the energy conservation. The correctness of the proposed schemes is verified through AUTLOG analysis. It has been shown that the proposed schemes are secure against various types of attacks and consume significantly less energy than existing mechanisms in waking up an IoT device.

Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things.

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

Edge computing-based joint client selection and networking scheme for federated learning in vehicular IoT

In order to support advanced vehicular Internet-of-Things (IoT) applications, information exchanges among different vehicles are required to find efficient solutions for catering to different application requirements in complex and dynamic vehicular environments. Federated learning (FL), which is a type of distributed learning technology, has been attracting great interest in recent years as it performs knowledge exchange among different network entities without a violation of user privacy. However, client selection and networking scheme for enabling FL in dynamic vehicular environments, which determines the communication delay between FL clients and the central server that aggregates the models received from the clients, is still under-explored. In this paper, we propose an edge computing-based joint client selection and networking scheme for vehicular IoT. The proposed scheme assigns some vehicles as edge vehicles by employing a distributed approach, and uses the edge vehicles as FL clients to conduct the training of local models, which learns optimal behaviors based on the interaction with environments. The clients also work as forwarder nodes in information sharing among network entities. The client selection takes into account the vehicle velocity, vehicle distribution, and the wireless link connectivity between vehicles using a fuzzy logic algorithm, resulting in an efficient learning and networking architecture. We use computer simulations to evaluate the proposed scheme in terms of the communication overhead and the information covered in learning.

IoT combined with Block-Chain and 5G infrastructure for its application and development : A Review

It is a modern type of technology that empowers virtual and physical artefacts to interact and provide digitized services for each other, and includes the Internet of Things (IoT). But it has some benefits, but raises problems of single point of failure, anonymity, accountability, and data integrity due to the new structured design. Challenges like these stands in the path of the introduction of all the most interesting Internet of Things technologies. Bringing the Internet of Things through the public ledger might fix these issues. Decentralized ledger systems are comprised of blockchain as well as distributed ledgers. The introduction of the Internet of Things (IoT) to the blockchain will offer tremendous advantages. Blockchain integration in this paper offers a detailed exploration of how to combine the IoT technology with the IoT scheme. It is followed by reviewing the basic framework and addressing the problems inherent in the system's integration, explaining the advantages of it, and describing ways in which the blockchain can help to overcome such problems. Blockchain as a Service for IoT can illustrate how different protocol concepts can be applied using different service types on blockchain. After this, there would be an important section about the integration of artificial intelligence (AI) into the Internet of Things (IoT) and blockchain. Finally, potential study avenues will focus on ways of applying the Internet of Things (IoT) with blockchain are suggested. The open issues and challenges of 5G-enabled IoT for blockchain-based Industrial automation are also analyzed in the text.

An enhanced authentication scheme for Internet of Things and cloud based on elliptic curve cryptography

SummaryAuthentication plays a fundamental role in achieving security over unreliable channels. Authentication is a technique that lets an entity verify the identity of other communicating entities. There are a plethora of authentication schemes available in recent times. A short time ago, Kumari et al. offered an authentication protocol using elliptic curve cryptography (ECC) for Internet of Things (IoT) and professed that their design defends various security attacks. We examined Kumari et al.'s scheme and detected some loopholes like (1) inefficient login phase, (2) inefficient authentication phase, (3) known session‐specific temporary information attack, (4) denial‐of‐service (DoS) attack, and (5) lack of password changing phase. To eradicate all these flaws, we present an enhanced authentication protocol utilizing ECC for deployment in the field of IoT using cloud servers. This protocol uses hypertext transfer protocol (HTTP) cookies to authenticate clients. The developed protocol provides various security features and able to counter various security attacks. The security analysis validates that the extended scheme is potent. We simulate our protocol in Automated Validation of Internet Security Protocols and Applications (AVISPA) tool that evaluates the safety of the scheme in the presence of an adversary. We compare the proposed scheme with some similar schemes in respect of computation cost, estimated time, storage cost, communication cost, and security features.

Efficient Digital Signature Scheme for Internet of Things

Apparently enthusiasm for the Internet of things (IoT) has as of late arrived at its top, with a lot of center from both the private and public parts. IoT, an innovation that empowers the trading of information through linkage among all items encompassing the client, can make new administrations. Information correspondence among objects isn't restricted to individual data, yet can likewise convey diverse information types, for example, detecting data gathered from the general condition. At the point when such information is gathered and utilized malevolently by an assailant, it is more defenseless against dangers than in traditional organization situations. In this article we proposed for digital signature scheme for Internet of Things.

A secure and efficient authentication and data sharing scheme for Internet of Things based on blockchain

Internet of Things (IoT) is a network convergence of multiple intelligent devices and advanced technologies aiming at connecting and exchanging data over the Internet. IoT is extensively applied in consumer, commercial, industrial, infrastructure and military spaces. With the prevalence of IoT applications, security issues such as identity authenticity and data privacy are increasingly become critical concerns. Authentication and confidential data sharing are the important measures towards secure IoT communication and applications. Blockchain is a burgeoning technology supporting for efficient authentication and secure data sharing. A secure and accountable data transmission scheme based on blockchain has been proposed by Hong et al. recently. But this scheme has security weaknesses of impersonation attack, man-in-the-middle attack, replay attack, denial of service attack (DoS) and key compromise attack. Thus we put forward an improved scheme to overcome the identified security flaws. Our scheme is provably secure and performance analysis shows that our scheme reduces 15.34% computation costs and 40.68% communication costs compared with Hong et al.’s scheme. Meanwhile, we also compare our scheme with other three recent and related researches, which finally indicates that our scheme realizes a well tradeoff between security and efficiency.

Two-Level-Composite-Hashing Facilitating Highly Efficient Anonymous IoT and D2D Authentication

Resource limitation is quite popular in many Internet of Things (IoT) devices and eavesdropping on the identities of IoT devices could reveal the sensitive information; therefore, high efficiency (computation and communication) and anonymity protection are two desirable properties in IoT authentication and in device-to-device (D2D) authentication. Conventionally, dynamic pseudonyms are widely adopted to protect the device identity privacy in IoT authentication and in D2D communications; however, the conventional mechanisms of pseudonym-renewing and pseudonym-bound-public-keys updating could be very costly or be vulnerable to the desynchronization-based denial-of-service (DoS) attacks. In this paper, we propose a novel 2-level composite hashing (2LCH) mechanism to mitigate the problems, and propose the 2LCH-based anonymous IoT and D2D authentication schemes. The schemes simultaneously achieve high efficiency and strong anonymity for such environments; once two devices successfully complete one instance of the server-assist anonymous authentication, they can run several instances of the direct D2D anonymous authentication without the involvement of the server. The merits of the schemes include: (1) high efficiency in terms of computation and communication; (2) easy and efficient generation/synchronization of dynamic pseudonyms; (3) robustness to both desynchronization-based DoS attacks and the unreliable connections; (4) easy application to the existent IoT architectures and standards; and (5) formal security verification.

A lightweight key management scheme for key-escrow-free ECC-based CP-ABE for IoT healthcare systems

The rapid increase in the implementation of Internet of Things (IoT) solutions in diverse healthcare sectors raises the IoT in the healthcare market. The real-time health monitoring to manage the chronic diseases is likely to drive the demand of IoT in healthcare. Moreover, the enhancement in communication technologies like real-time data transmission has improved the patients’ confidence in managing the chronic disease and medication dosage. Although IoT in healthcare makes a positive impact on patients and healthcare providers, however, it gets the challenges like data security and privacy. One means of sustaining security in IoT based healthcare system is through key management and at the same time an effective security mechanism for outsourced data to obtain fine-grained access control is the Ciphertext Policy-Attribute Based Encryption (CP-ABE). However, the overhead of complex decryption operations and key-escrow problem of CP-ABE hinders its applicability in IoT. Hence, in this work, we design a lightweight key management mechanism for the CP-ABE scheme using Elliptic Curve Cryptography (ECC). The novelty in this scheme is that irrespective of the secret key generation by the semi-trusted authority (honest, but curious to know the secret information), it is not capable to decrypt any message using these keys until and unless it has an additional private key of the receiver. For a constraint environment like IoT, the applicability of CP-ABE has two major issues: complex decryption operations and key-escrow problem. Hence, in this paper, a lightweight CP-ABE scheme for IoT based health care system using ECC has been designed. The proposed key management mechanism in the CP-ABE scheme is key-escrow free as well as significantly reduces the decryption overhead of the data receiver. The performance analysis shows that the proposed scheme is more effective as compared to the existing competing schemes.

Secure Multifactor Authenticated Key Agreement Scheme for Industrial IoT

The application of Internet of Things (IoT) has generally penetrated into people’s life and become popular in recent years. The IoT devices with different functions are integrated and applied to various domains, such as E-health, smart home, Industrial IoT (IIoT), and smart farming. IIoT obtains the general attention among these domains, which allows the authorized user remotely access and control the sensing devices. The user suffices to attain the real-time data collected by sensing devices during the process of production. However, these data is usually transmitted via an insecure channel, which brings the problem of the security and privacy arising from the hostile attacks in IIoT. To resist the hostile attacks by the adversary and protect the security of the transmitted data, we propose a secure multifactor authenticated key agreement scheme for IIoT to support the authorized user remotely accessing the sensing device. The scheme adopts password, biometrics, and smart card to identify the user in the IIoT environment. We employ the secret-sharing technology and Chinese remainder theorem to construct a group key among legitimate sensing devices, and then this group key is utilized to assist in negotiating a secure session key between the user and multiple sensing devices. The proposed scheme is suitable for the resource-constrained IIoT as it only uses hash function, bitwise XOR operation, and symmetric cryptography. The performance analysis indicates that our scheme has less communication and computational costs in contrast to other correlative schemes. Besides, the security analysis indicates that our scheme can withstand many known attacks.

Distributed Q-Learning Based Joint Relay Selection and Access Control Scheme for IoT-Oriented Satellite Terrestrial Relay Networks

In this letter, we propose a distributed Q-learning (DQL) based joint relay selection and access control (JRSAC) scheme for Internet of Things (IoT)-oriented satellite terrestrial relay networks (STRNs) with massive IoT devices and multiple relays. Firstly, a semi-random access (SRA) architecture is proposed to improve the learning efficiency of the DQL algorithm. Subsequently, a JRSAC optimization problem is formulated and solved by the proposed DQL algorithm. Simulation results show that the proposed DQL based JRSAC scheme significantly outperforms conventional schemes in terms of the medium access control (MAC) throughput, total access delay, and sum rate.