The cognitive radio-enabled$massive$Internet of Things (CR-$m$IoT) is envisioned to shape the future of densely connected IoT devices in the sixth-generation networks to support the hyperconnected society. In conventional CR networks, secondary users (SUs) sense the whole block of spectrum to find idle channels, which is an energy-consuming, delay-inducing, and processing-intensive task. With the large scale of resource-constrained heterogeneous devices in CR-$m$IoT, the sensing process becomes a major hurdle for CR-$m$IoT devices to achieve efficient utilization of the limited device and network resources. Thus, a novel multiparameter-based flexible scheme is proposed for idle channel prediction and channel ranking, which considers priorities as well as heterogeneity of users. The scheme uses a probabilistic approach and employs multiple parameters simultaneously to evaluate the suitability of a channel before selecting it for transmission. In addition, valid channel obsolescence, a major problem inherent with channel prediction and ranking, is countered by the proposed scheme. The scheme is evaluated under the impact of variable primary and SUs’ arrivals and under multiple channel failures rates and variable sensing and frame time duration. The proposed scheme is also compared with its own modified version that disregards channel failures, and with the random channel selection approach followed by IEEE 802.22. The overall evaluation is conducted under realistic spectrum sensing. Simulation results show that for different parameter values, the proposed scheme improves the collision probability by 11%–55%, reduces sensing time and energy by 60% and 65%, respectively, and enhances throughput by 4%–70%, and spectrum utilization efficiency by 11%–40%.

With the widespread utilization of Internet-enabled smart devices (SDs), the Industrial Internet of Things (IIoT) has become prevalent in recent years. SDs exchange information through the open Internet, which creates security and privacy concerns for the exchanged information. To address these concerns, various solutions exist in the literature which, because of high computational and communication overheads, are not appropriate for the resource-constricted IIoT environment. This article proposes a resource-efficient authentication protocol for the IIoT, called REAP-IIoT, which employs a lightweight cryptography (LWC)-based authenticated encryption with associative data (AEAD) primitive AEGIS along with hash function. LWC-based AEAD primitives are suitable for resource constraint SDs because they require fewer computational resources. Moreover, REAP-IIoT renders the privacy-preserving user authentication functionality and establishes a session key (SK) between SDs deployed in the IIoT environment and users. Both user and SD utilize the established SK for encrypted communication. The security of SK, established during the authentication and key exchange (AKE) process of REAP-IIoT, is validated through the broadly accepted random or real model. Besides, Scyther-based security verification is conducted to illustrate that REAP-IIoT is secure and can protect the man-in-the-middle and replay attacks. Additionally, the informal security analysis is carried out to show that REAP-IIoT is protected against various covert security risks. A thorough comparison reveals that REAP-IIoT renders enhanced security characteristics apart from its low communication, storage, and computational overheads than the relevant AKE protocols.

Internet of Drones (IoD) is the interconnection of unmanned aerial vehicles or drones deployed for collecting sensitive data to be used in critical applications. The drones transmit the collected data to the control room (CR) for analysis, while CR sends control commands to the drone to monitor their operations. This exchange of information between the drones and CR takes place through a wireless communication channel, which is susceptible to various security risks. Therefore, it is vital to ensure the confidentiality and integrity of such information in the IoD environment. To this end, authenticated key management (AKM) protocols can be leveraged to provide reliable and secure communication. However, due to the peculiarities associated with IoD environments, it is challenging to devise a robust and resource-efficient AKM protocol. To tackle this challenge, in this article, we propose a robust AKM protocol for IoD (RAMP-IoD). RAMP-IoD uses lightweight cryptography-based authenticated encryption primitive and elliptic-curve cryptography along with a hash function to perform the AKM process. Moreover, RAMP-IoD verifies the user’s authenticity and then sets up a session key (SK) between the user and a specific drone for indecipherable communications. We verify the security of SK using the random oracle model. Scyther-based validation demonstrates that RAMP-IoD is protected against replay and man-in-the-middle attacks. Moreover, the informal analysis illustrates that RAMP-IoD is secure against various covert security attacks. Through a comparative study, we also demonstrate that RAMP-IoD provides enhanced security with low storage, communication, and computational overheads as compared to related AKM protocols.

Lightweight cryptography (LWC)-based authenticated encryption with associative data (AEAD) cryptographic primitives require fewer computational and energy resources than conventional cryptographic primitives as a single operation of an AEAD scheme provides confidentiality, integrity, and authenticity of data. This feature of AEAD schemes helps design an access control (AC) protocol to be leveraged for enhancing the security of the resource-constrained Internet of Things (IoT)-enabled smart grid (SG) system with low computational overhead and fewer cryptographic operations. This article presents a novel and robust AC protocol, called RACP-SG, which aims to enhance the security of resource-constrained IoT-enabled SG systems. RACP-SG employs an LWC-based AEAD scheme, ASCON and the hash function, ASCON-hash, along with elliptic curve cryptography to accomplish the AC phase. Besides, RACP-SG enables a smart meter (SM) and a service provider (SEP) to mutually authenticate each other and establish a session key (SK) while communicating across the public communication channel. By using the SK, the SM can securely transfer the gathered data to the SEP. We verify the security of the SK using the widely accepted random oracle model. Moreover, we conduct Scyther-based and informal security analyses to demonstrate that RACP-SG is protected against various covert security risks, such as replay, impersonation, and desynchronization attacks. Besides, we present a comparative study to illustrate that RACP-SG renders superior security features while reducing energy, storage, communication, and computational overheads compared to the state of the art.

Cognitive radio networks (CRNs) can facilitate ultra-reliable communication among IoT devices in the 6G environment by enhancing channel availability (CA) for primary and secondary users. However, CA does not necessarily lead to successful connection establishment unless receiver’s accessibility (RA) is guaranteed. This motivates us to propose the notion of connection availability (CoA) that incorporates RA into CA. We also introduce the idea of service maintainability (SM) that includes the effect of RA in service retainability. Additionally, spectrum utilization efficiency (SUE) is expressed and analyzed with and without considering the impact of RA. For performance evaluation, a channel reservation algorithm with customizable configurations is proposed. Furthermore, an analytical model is used to investigate the network performance for all key performance indicators (KPIs) under multiple channel failures and PU arrival rates and determine valuable tradeoffs among KPIs.

Cognitive radio networks (CRNs) promise to accommodate billions of Internet of Things (IoT) devices within scarce spectrum by allowing secondary users (SUs) to use licensed spectrum. However, the devices need uninterruptible communication, which the conventional CRNs cannot fulfill. This necessitates successful service completion probability (SSCP) enhancement in CRNs. Further, maintaining fairness among SUs, in terms of availing network services, is a matter of consideration for ensuring the network services to be fairly available to all SUs. In this paper, we propose a hybrid CRN (HCRN) scheme to analyze two problems. Firstly, we investigate SSCP enhancement by utilizing hybrid underlay-interweave mode of CRNs and propose a dynamic channel reservation algorithm to support interrupted users. Secondly, we propose a multi-attributes based fairness-driven channel determination (MFD) algorithm for channel interruption, which ensures fairness among SUs in availing network services. Furthermore, continuous-time Markov chain is used for modelling, and mathematical formulations are derived for SSCP. The proposed scheme is evaluated under various network traffic loads and channel failure rates. Numerical results show significant improvement in SSCP and reduction in forced termination rate as compared to the benchmark. Similarly, the MFD algorithm brings a prominent improvement in fairness.