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.

Abstract

With the emergence of the concept of smart city and the increasing demands for a range of drones, Internet of Drones (IoD) has achieved a variety of attention by providing multiple benefits in academia and industry. IoD offers numerous services, such as traffic monitoring, environmental monitoring, and disas- ter management by combining infrastructure, Internet of Things (IoT), and Flying Ad-Hoc Networks (FANET) in smart city envi- ronments. However, communication among drones is vulnerable to potential security threats because the sensitive messages in various applications are exchanged via an insecure channel in IoD-based smart city environments. Since IoDs can be operated in unat- tended environment with minimum human interventions, smart devices (e.g., drones and sensors) deployed in IoD architectures are vulnerable to physical capture attacks. In addition, drones are resource-constrained in terms of computation and communication overheads, and it is not much viable to apply public key cryptog- raphy (PKC) that requires high computation and communication overheads. Thus, we design a secure and lightweight authentication protocol using a physical unclonable function (PUF) for IoD to guarantee reliable and useful services in smart city environments, called SLAP-IoD. We prove the security of the SLAP-IoD using informal and formal security analyses using the broadly recog- nized Real-Or-Random (ROR) random oracle model, and also through the formal security verification using the widely-accepted Automated Validation of Internet Security-sensitive Protocols and Applications (AVISPA) security verification. Furthermore, we com- pare the performance of the SLAP-IoD with related schemes. Consequently, we show that SLAP-IoD offers better security and efficiency than other related schemes and is suitable for IoD-based smart city environments

Abstract

The Internet of Medical Things (IoMT) is a kind of communication environment, which deals with communication that occurs through the Internet of Things (IoT)-enabled smart medical (healthcare) devices. The potential security threats of IoMT affect the confidentiality, integrity, authenticity and availability of its data and the associated resources. In this review article, we explain various architectures of IoMT communication along with their applications. We highlight the security requirements of IoMT communication environment along with some potential security attacks and threats of IoMT. Furthermore, the network model and adversary model of IoMT communication are provided. A taxonomy of security protocols of IoMT communication environment is additionally added, which contains various security protocols, such as key management, user/device authentication, access control and intrusion detection protocols. Moreover, we provide a detailed comprehensive comparative analysis of several security protocols with respect to various parameters, like computation cost, communication cost, security features and functionality features, accuracy and F1-score. Additionally, we also provide some future research directions.

Abstract

Emerging 5G/6G communication and next-generation Internet (NGI) technologies demand proper administration and control of an ultra large-scale dynamic network to provide high-speed ubiquitous networked-resource accessing while assisting higher channel bandwidth. The conventional static network infrastructure-based solutions provide only manual supervision and third-party provisioning of the networked assets. In addition, such settings mostly forefront to unsuitable resource usage, and sometimes lead to several security and privacy concerns. The de facto Software-Defined Networking (SDN) has come up with several new promises to solve such limitations. Since its inception, SDN decouples the traditional data layer from the control plane of a third-party network equipment, which is claimed to be ensured higher security, dynamicity, scalability, efficiency, and faster reconfiguration capability of a ultra large-scale dynamic network as compared with the conventional network. However, a thorough inspection of the literature presently shows that most of the vulnerabilities are originated from the two specific layers, namely, control and data plane of the underlying SDN framework. Also, due to the absence of proper authentication and access control mechanisms ensuring inevitable protection of the SDN controller node and the network assets is a very challenging task. Though secure socket layer (SSL) or transport layer security (TLS)-based solutions are predominantly advocated in this domain to assist security in SDN framework but such mechanisms are also vulnerable to spoofing, sniffing, eavesdropping, replay, man-in-the-middle, privileged-insider, denial-of-service, distributed-denial-of-service, impersonation attacks. Therefore, this work qualitatively countermeasures all the recently attended (or unattended) state-of-the-art security and privacy concerns related to the recently reported access control, authentication, key management, secure data aggregation, privacy-aware secure auditing, and layer-wise functional inconvenience policies with respect to each and every layers of SDN platform. This study hence will be helpful to the academicians and researchers for the future development of new policies and protocols in the SDN platform.

Abstract

Low-power wireless sensor networks (WSNs) and Internet of Things (IoT) have great impact for the real-time applications in future 5th generation (5G) mobile networks due to the wireless-powered communication technologies. The Age of Information (AoI) plays a crucial performance metric in an IoT-enabled real-time smart warehouse application, where the freshness of the aggregated data is very important. However, wireless medium communication among the beacon nodes and the user equipments (tracking nodes) gives an opportunity to an adversary not only to eavesdrop the data but also to corrupt the data by means of deleting, modifying or inserting malicious information during communication among the entities involved in the smart warehouse environment. To mitigate these issues, we design a security scheme for AoI-enabled 5G smart ware- house through an access control mechanism, where the secure communication among the beacon nodes and the tracking nodes will take place by mutual device authentication and key agree- ment process. The fresh data collected at the enterprise cloud is then used for big data analytics for better predictions and anal- ysis, such as optimal device scheduling so that the data becomes very fresh. The rigorous security analysis and comparative study show that the proposed mechanism has significantly better secu- rity and comparable communication and computational costs as compared to the relevant schemes. In addition, through the real- time testbed experiments, we show that the proposed scheme is practical in 5G smart warehouse context. Index Terms—Access control and key agreement (ACKA), Age of Information (AoI), bi

Abstract

The primary objective of postquantum cryptography (also known as quantum-resistant cryptography) is to develop the cryptographic systems that need to be robust against both quantum and classical computers, and can also interoperate with the existing communications protocols and networks. In an Internet of Things (IoT) environment, the communicated messages contain sensitive information that are transmitted over an open channel, where message integrity and data privacy become challenging tasks. Although several traditional cryptographic security protocols can be applied for IoT security and data privacy, such as authentication, access control, key agreement, and digital signature, but they are not resilient against quantum attacks. To overcome these issues, in this article, we first present an advanced and efficient construction of postquantum lattice-based signcryption scheme, and then apply the constructed lattice-based signcryption in IoT applications, where data sensed by the deployed IoT smart devices is securely stored at the cloud, via the gateway nodes (aggregators). The data stored at the cloud servers cannot be even modified by them due to the involved signatures generated by the aggregators. The formal security analysis shows the robustness of our designed lattice-based signcryption scheme. Other detailed information security analysis and a performance analysis with the traditional number-theoretical based public key cryptosystems show the efficacy, and significantly better security and functionality features of the proposed scheme under the lattice-based postquantum context.