Abstract

Precision farming has a positive potential in the agricultural industry regarding water conservation, increased productivity, better development of rural areas, and increased income. Blockchain technology is a better alternative for storing and sharing farm data as it is reliable, transparent, immutable, and decentralized. Remote monitoring of an agricultural field requires security systems to ensure that any sensitive information is exchanged only among authenticated entities in the network. To this end, we design an efficient blockchain-enabled authenticated key agreement scheme for mobile vehicles-assisted precision agricultural Internet of Things (IoT) networks called AgroMobiBlock . The limited existing work on authentication in agricultural networks shows passive usage of blockchains with very high costs. AgroMobiBlock proposes a novel idea using the elliptic curve operations on an active hybrid blockchain over mobile farming vehicles with low computation and communication costs. Formal and informal security analysis along with the formal security verification using the Automated Validation of Internet Security Protocols and Applications (AVISPA) software tool have shown the robustness of AgroMobiBlock against man-in-the-middle, impersonation, replay, physical capture, and ephemeral secret leakage attacks among other potential attacks. The blockchain-based simulation on large-scale nodes shows the computational time for an increase in the network and block sizes. Moreover, the real-time testbed experiments have been performed to show the practical usefulness of the proposed scheme.

Abstract

Elliptic Curve Cryptography (ECC)-based authenti-cation schemes for the Radio-frequency identification (RFID) environment have emerged as a very safe, secure, and robust candidate of mutual authentication. However, the limited resource availability in a passive tag makes such schemes difficult to realize in practice. Public/private key pair generation, storage, and the computation using those keys are the major bottlenecks towards the faster and efficient design of such schemes. Therefore, we have designed our scheme without using public/private key pairs. We only utilize the Elliptic Curve Discrete Logarithm Problem (ECDLP) property for the realization of our key-less scheme on the secure elliptic curves. Our scheme is primarily aimed at efficient implementation of authentication schemes in Warehouse Management System (WMS), where the data is stored in local servers. This new idea helps to save the memory space in the tags and the server. Moreover, the computation cost also reduces to a great extent in comparison to other schemes. We have compared our scheme with several other schemes and found it efficient in terms of storage cost as well. The simulation result of our scheme with the popular aut

Abstract

The distributed nature of Internet of Things (IoT) and fog computing mandates that the security provided to the resources of networking and data on these applications is based on a distributed structure. The nodes in a fog computing environment should be working with equal capacities without any necessity of trust among them, in order to allow the layers and infrastructure that constitute the stack of a fog node to be owned and managed by different entities. This idea of security necessitates the need for distributed trust in fog computing that can be realized using the concept of blockchain technology. Blockchain is a distributed and

Abstract

The information system of healthcare operates through various frameworks, like wireless body area network, telecare medical information system, and mobile or electronic healthcare. All these systems need to maintain the personal health records (PHRs) for various users (ie, patients, doctors, and nurses). In such systems, we need to process and store the health related sensitive data (ie, PHRs). In this article, we aim to provide a robust security mechanism to secure exchange and storage of healthcare data, especially PHRs. We present a generic architecture of blockchain‐enabled secure communication mechanism for Internet of Things‐driven personal health records (BIPHRS). We then discuss various threats and security attacks of healthcare system along with different available security mechanisms. The conducted security analysis and detailed comparative study of the state of art blockchain enabled security schemes for PHR systems show that the proposed BIPHRS provides a better security and more functionality features as compared to other similar existing approaches. We propose a blockchain‐enabled secure communication framework for Internet of Things‐driven personal health records (BIPHRS). The proposed BIPHRS provides better security and more functionality features as compared to the other similar schemes. In addition, a practical

Abstract

Industry 5.0 is the automation, digitization, and data communication of the industrial procedure that comprises industrial cyber–physical systems (I-CPSs), industrial Internet of Things (IIoT), and artificial intelligence (AI). In the I-CPS-enabled healthcare ecosystem, intelligent wearable devices have been extensively employed to sense body information and measure the health status of the patients. Besides other IIoT applications, the I-CPS-enabled healthcare ecosystem also bears various challenges. For instance, due to the communal communication mediums, the security of a patient’s physiological datum is becoming a significant challenge these days. In order to cope with this challenge, we presented a secure and lightweight key establishment protocol. To the best of our knowledge, this protocol is the first application of physically unclonable function (PUF) in the I-CPS-enabled healthcare. The security of the designed protocol is proved with the help of a widely recognized real-or-random (ROR) model. The practical demonstration of our protocol from the network perspective is also measured through broadly recognized NS3 simulator tool.

Abstract

This article proposes a new blockchain-envisioned key management protocol for artificial intelligence (AI)-enabled industrial cyber–physical systems (ICPSs). The designed key management protocol enables key establishment among the Internet of Things (IoT)-enabled smart devices and their respective gateway nodes. The blocks partially constructed with secure data from smart devices by fog servers are provided to cloud servers that are responsible for completing blocks, and then mining those blocks for verification and addition in the blockchain. The most important application of the private blockchain construction is to apply AI algorithms for accurate predictions in Big data analytics. A detailed security analysis along with formal security verification show that the proposed scheme resists various potential attacks in an ICPS environment. Moreover, practical testbed experiments have been conducted using the multiprecision integer and rational arithmetic cryptographic library (MIRACL). Furthermore, a detailed comparative analysis shows superiority of the proposed scheme over recent relevant schemes. In addition, the practical implementation using the blockchain for the proposed scheme demonstrates the total computational costs when the number of transactions per block and also the number of blocks mined in the blockchain are varied.

Abstract

Web of Things (WoT) extends the Internet of Things (IoT) paradigm to facilitate communications among smart things/devices and Web-based applications. In other words, WoT systems generally provide a Web interface for the monitoring and controlling of smart devices over the Web, for example, in applications, such as home automation, intelligent transportation system, smart healthcare, smart cities, and smart agriculture. However, this results in the generation of significant volume of data (i.e., big data) and, hence, the importance of big data analytics. There are also associated security and privacy implications. Therefore, in this article, we present a signature-based authentication and key agreement scheme for the WoT environment and prove its security. We also evaluate the performance of SCS-WoT and compare it against four other competing schemes. The findings show that SCS-WoT achieves better performance in terms of communication cost, computational cost, and security and functionality.

Abstract

Recently, Internet of Drones (IoD) has emerged as an important topic to research in academy and industry due to its generic ser- vices for various drone applications. In an IoD environment, the deployed drones and the ground station server (GSS) communicate over an open network which leads to security and privacy breaches. To mitigate these issues, a blockchain driven authentication and key establishment protocol for secure communication in IoD has been designed (in short, it is called as BAKP-IoDA). The security analysis of BAKP-IoDA shows its robustness against different at- tacks. During the performance comparison, it has been observed that BAKP-IoDA maintains superior security along with extra func- tionality features with the competing schemes. Additionally, the blockchain based practical demonstration of BAKP-IoDA shows its impact on various important network performance parameters, like computation time and transactions per second

Abstract

Machine learning (ML) is a subset of Artificial Intelligence (AI), which focuses on the implementation of some systems that can learn from the historical data, identify patterns and make logical decisions with little to no human interventions. Cyber security is the practice of protecting digital systems, such as computers, servers, mobile devices, networks and associated data from malicious attacks. Uniting cyber security and ML has two major aspects, namely accounting for cyber security where the machine learning is applied, and the use of machine learning for enabling cyber security. This uniting can help us in various ways, like it provides enhanced security to the machine learning models, improves the performance of the cyber security methods, and supports effective detection of zero day attacks with less human intervention. In this survey paper, we discuss about two different concepts by uniting cyber security and ML. We also discuss the advantages, issues and challenges of uniting cyber security and ML. Furthermore, we discuss the various attacks and provide a comprehensive comparative study of various techniques in two different considered categories. Finally, we provide some future research directions. © 2022 The Author(s). Published by Elsevier B.V. on behalf of The Korean Institute of Communications and Information Sciences. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Keywords: Cyber security; Machine learning; Internet of Things (ioT); Privacy; Security; Intrusion detection

Abstract

The Internet of Things (IoT) is a network of interconnected, Internet-connected items (i.e., smart devices) that can collect and transmit data across a wireless network with- out the need for human intervention. IoT enables the systems to have higher efficiency and dependability in their day-to-day operations due to its strong focus on machine-to-machine (M2M) connectivity, big data, and machine learning. While IoT has many advantages over traditional techniques, it also has a number of security and privacy concerns. Trust is a belief in the competence of a device (computing machine) to act dependably, securely and reliably in some specific context. In an M2M (one IoT device to other IoT device) communication, trust is accomplished by making the use of cryptographic operations (i.e., digital signa- tures and electronic certificates). Various security threats and attacks have been launched on IoT connectivity in recent years. A trust mechanism is necessary to ensure the quality of collab- orative service behaviors and to build confidence between IoT devices. As a result, how to create an effective trust computing mechanism has become an emerging topic in IoT. Therefore, we provide the design of a novel trust-aggregation-based authen- tication scheme for secure communication of edge-enabled IoT (in short, TACAS-IoT). The security analysis shows that TACAS- IoT is secured against a variety of attacks. Moreover, TACAS-IoT delivers greater security and capabilities with less communica- tion and computation overheads, according to the performance comparison. Finally, a practical implementation of TACAS-IoT is provided in order to assess its impact on the key performance parameters. Index Terms—Authentication and key management, Internet of Things (IoT), security, simulation, trust.