Ubiquitous connectivity is the most significant goal of sixth-generation (6G) wireless networks. To this end, integrating non-terrestrial networks (NTNs) with terrestrial networks (TN) can be an inevitable path to 6G. To achieve cost-effectiveness and bandwidth efficiency in NTN design, the open radio access network (O-RAN) and integrated access and backhaul (IAB) approaches, which prevail in TN, are adopted in the proposed NTN architecture. To maximize the uplink rate under bandwidth and power constraints, we jointly optimize i) the power allocation to pilot and data symbols, ii) the compression rates for inter-satellite link (ISL) transmission of pilot and data, and iii) the bandwidth partitioning between the access link and the xHaul link. Because the original optimization problem is challenging to solve directly, it is decomposed into three subproblems: power, compression rate, and bandwidth optimization, while the other parameters being kept fixed. The convergent solution is obtained via an iterative optimization approach that alternates between optimization and a gradient-based search. The effectiveness of the proposed approach is verified by numerical simulations.

Reconfigurable intelligent surfaces (RISs) are emerging as a transformative technology for sixth-generation (6G) wireless networks. They enable dynamic manipulation of the propagation environment to enhance signal coverage, mitigate interference, and improve spectral and energy efficiencies. However, this flexibility introduces significant security vulnerabilities when RISs are maliciously controlled. This study explores the threats posed by such RISs, focusing on their potential to compromise the security and integrity of 6G networks. From an adversarial perspective, we analyze key attack vectors, including sophisticated jamming attacks that disrupt communication, eavesdropping attacks that intercept communications, and pilot contamination attacks that impair channel estimation accuracy, all contributing to severe performance degradation. For each attack, we detail the underlying mechanisms and adversarial optimization strategies designed to maximize impact. A case study quantifies the practical effects of these malicious RIS-based attacks in a simulated 6G network scenario. This research emphasizes the critical need for robust defense mechanisms and proposes essential research directions to address the evolving threats from malicious RISs, ensuring the security of 6G networks.

A common practice among programmers is to reuse existing code, accomplished by performing natural language queries through search engines. The main aim of code retrieval is to search for the most relevant snippet from a corpus of code snippets. However, code retrieval frameworks for low-resource languages are insufficient. Retrieving the most relevant code snippet efficiently can be accomplished only by eliminating the semantic gap between the code snippets residing in the repository and the user’s query (natural language description). The primary objective of the research is to contribute to this field by providing a code search framework that can be extended for low-resource languages. The secondary objective is to provide a code retrieval mechanism that is semantically relevant to the user query and provide programmers with the ability to locate source code that they want to use when developing new applications. The proposed approach is implemented using a web platform to search for source code. As code retrieval is a sophisticated task, the proposed approach incorporates a semantic search mechanism. This research uses a semantic model for code retrieval, which generates meanings or synonyms of words. The proposed model integrates ontologies and Natural Language Processing. System performance measures and classification accuracy are computed using precision, recall, and F1-score. We also compare the proposed approach with state-of-the-art baseline models. The retrieved results are ranked, showing that our approach significantly outperforms robust code matching. Our evaluation shows that semantic matching leads to improved source code retrieval. This study marks a substantial advancement in integrating programming expertise with code retrieval techniques. Moreover, our system lets users know when and how it is used for successful semantic searching.

The communication among smart meters (SMs) and neighborhood area network (NAN) gateways is a fundamental requisite for managing the energy consumption at the consumer site. The bidirectional communication among SMs and NANs over the insecure public channel is vulnerable to impersonation, SM traceability, and SM physical capturing attacks. Many existing schemes’ insecurities and/or inefficiencies call for an efficient and secure authentication scheme for smart grid infrastructure. In this article, we present a privacy preserving and lightweight authentication scheme for smart grid (LAS-SG) using elliptic curve cryptography. The proposedLAS-SGis proved as secure under the standard model. Moreover, the efficiency of the LAS-SG is extracted through a real-time experiment, which attests that proposedLAS-SGcompletes a round of authentication in 20.331 ms by exchanging only two messages and 192 B. Due to the adequate efficiency and ample security, the proposedLAS-SGis more appropriate for SG environments.

Impressive technological advancements over the past decades commenced significant advantages in the maritime industry sector and elevated commercial, operational, and financial benefits. However, technological development introduces several novel risks that pose serious and potential threats to the maritime industry and considerably impact the maritime industry. Keeping in view the importance of maritime cyber security, this study presents the cyber security threats to understand their impact and loss scale. It serves as a guideline for the stakeholders to implement effective preventive and corrective strategies. Cyber security risks are discussed concerning maritime security, confidentiality, integrity, and availability, and their impact is analyzed. The proneness of the digital transformation is analyzed regarding the use of internet of things (IoT) devices, modern security frameworks for ships, and sensors and devices used in modern ships. In addition, risk assessment methods are discussed to determine the potential threat and severity along with the cyber risk mitigation schemes and frameworks. Possible recommendations and countermeasures are elaborated to alleviate the impact of cyber security breaches. Finally, recommendations about the future prospects to safeguard the maritime industry from cyber-attacks are discussed, and the necessity of efficient security policies is highlighted.

The Sixth-Generation (6G) mobile network has the potential to provide not only traditional communication services but also additional processing, caching, sensing, and control capabilities to a massive number of Internet of Things (IoT) devices. Meanwhile, a 6G mobile network may provide global coverage and diverse quality-of-service provisioning to the Maritime Transportation System (MTS) when enabled through satellite systems. Although modern MTS has gained significant benefits from Internet of Things (IoT) and 6G technologies, threats and challenges in terms of security and privacy have also been grown substantially. Tracking the location of vessels, GPS spoofing, unauthorized access to data, and message tampering are some of the potential security and privacy vulnerabilities in the 6G-IoT enabled MTS. In this article, we propose a lightweight authentication protocol for a 6G-IoT enabled maritime transportation system to efficiently assist and ensure the security and privacy of maritime transportation systems. To validate the security characteristics, formal security assessment methods are utilized, i.e., Real-Or-Random (ROR) oracle model. The findings of the security analysis show that the proposed scheme is more secure than the existing schemes.

The rising popularity of ICT and the Internet has enabled Unmanned Aerial Vehicle (UAV) to offer advantageous assistance to Vehicular Ad-hoc Network (VANET), realizing a relay node’s role among the disconnected segments in the road. In this scenario, the communication is done between Vehicles to UAVs (V2U), subsequently transforming into a UAV-assisted VANET. UAV-assisted VANET allows users to access real-time data, especially the monitoring data in smart cities using current mobile networks. Nevertheless, due to the open nature of communication infrastructure, the high mobility of vehicles along with the security and privacy constraints are the significant concerns of UAV-assisted VANET. In these scenarios, Deep Learning Algorithms (DLA) could play an effective role in the security, privacy, and routing issues of UAV-assisted VANET. Keeping this in mind, we have devised a DLA-based key-exchange protocol for UAV-assisted VANET. The proposed protocol extends the scalability and uses secure bitwise XOR operations, one-way hash functions, including user’s biometric verification when users and drones are mutually authenticated. The proposed protocol can resist many well-known security attacks and provides formal and informal security under the Random Oracle Model (ROM). The security comparison shows that the proposed protocol outperforms the security performance in terms of running time cost and communication cost and has effective security features compared to other related protocols.

Summary Soft errors in network‐on‐chip (NoC) such as single bit upsets and multibit upsets cause hazardous effects such as congestion, deadlock, livelock, and corruption of data. Error‐correcting codes (ECCs) are the best choices to handle these soft errors in links and memory buffers of NoC, which is the need of all modern systems, including internet of thing (IoT) edge devices. Many of these ECCs cannot correct both random and burst errors. Specific codes possess the correction and detection capability at the cost of an increase in area, latency, and energy. In this article, a coding technique is proposed by using a single error correction double error detection‐triple adjacent error correction‐six adjacent error detection (SEC‐DED‐TAEC‐6AED) (24,16) I5, that provides both random and burst error fault tolerance for NoC. The proposed technique decreases the area, energy, and latency cost of the whole NoC. It also reduces the area overhead to 173.41% and 117.91% compare to joint crosstalk avoidance multiple error correction (JCAMEC) and joint crosstalk multiple error correction (JMEC), respectively. Besides, the delay overhead of the proposed technique reduces to 4.2% and 91.97% compared with JCAMEC and JMEC, respectively. The simulation results show that the proposed code possesses an enhanced ability of error correction and detection with 3.5 times less redundant bits and a 30% fast code rate compared with JMEC and JCAMEC. Hence, the proposed scheme can effectively be used for detecting and correcting single and multiple bit errors for on‐chip communication.

The advancements in the internet of things (IoT) require specialized security protocols to provide unbreakable security along with computation and communication efficiencies. Moreover, user privacy and anonymity has emerged as an integral part, along with other security requirements. Unfortunately, many recent authentication schemes to secure IoT-based systems were either proved as vulnerable to different attacks or prey of inefficiencies. Some of these schemes suffer from a faulty design that happened mainly owing to undue emphasis on privacy and anonymity alongside performance efficiency. This article aims to show the design faults by analyzing a very recent hash functions-based authentication scheme for cloud-based IoT systems with misunderstood privacy cum efficiency tradeoff owing to an unadorned design flaw, which is also present in many other such schemes. Precisely, it is proved in this article that the scheme of Wazid et al. cannot provide mutual authentication and key agreement between a user and a sensor node when there exists more than one registered user. We then proposed an improved scheme and proved its security through formal and informal methods. The proposed scheme completes the authentication cycle with a minor increase in computation cost but provides all security goals along with privacy.

To enable the internet of things (IoT) devices with increased coverage and optimized power consumption, the 3rdgeneration partnership (3GPP) standardizes the idea of narrowband IoT (NB-IoT) technology in the fifth generation (5G) of cellular communication. Re-transmission of control and data packets due to a poor link between user equipment (UE) and the base station (BS), is considered as one of the key feature in NB-IoT to ensure the data delivery of delay-sensitive applications, e.g. ambulance services and body sensor networks (BSN). This phenomenon degrades the energy efficiency of the already resource constrained systems. One key solution for NB-IoT UE is to exploit the device-to-device (D2D) communication using two hops instead of transmitting on a direct uplink, due to which the system performance increases. In an attempt to transmit the NB-IoT UE uplink data packet, splendid researchers have focused towards developing a D2D communication based strategy, which typically optimizes the expected packet delivery ratio (EDR) and end-to-end delay (EED) through an opportunistic method. However, such methodology imposes an additional delay due to the unavailability of active relaying nodes and increases the overall energy consumption of the system. This necessitates us to design an intelligent deterministic D2D (2D2D) relay selection strategy for delay sensitive NB-IoT UEs. The EDR and EED have been improved using deterministic programming based algorithm. Simulations with various parameters are carried out, and results are presented. Simulation results show that the deterministic algorithm gives better performance with a 10% increase in EDR and overcomes the additional delay.

Long Term Evolution (LTE) in unlicensed spectrum, Licensed Assisted Access (LAA), has been considered as an effective complement in offloading growing traffic. The LAA is expected to be deployed initially through the small cell integrated under LTE macro cell. Therefore, LTE users under the coverage of LAA small cell must decide to connect one of the co-located networks either LTE or LAA to maximize their performance. In this scenario, we model a network selection game for LTE users using mixed strategy game theoretic approach. Afterwards, we formulate behavior of strategic users toward network selection as a function of the number of nearby users. The simulation results show that increasing number of nearby users make a user less likely to switch to LAA small cell. Additionally, more users nearby make it less likely that LAA resources is being utilized.