This paper investigates the covertness and reliability of unmanned aerial vehicle (UAV) relay communications assisted by a friendly jammer in the presence of co-channel interference (CCI). In the considered scenario, communication from a source to a destination is relayed by a UAV, while a malicious node attempts to monitor the transmission behaviors of both the source and the UAV. To enhance the system’s covertness, we propose a friendly jammer aided covert communication (FJACC) scheme, which leverages a friendly jammer to degrade the detection capability of the malicious monitoring node by sending artificial noise. We analyze the covertness and reliability of the FJACC scheme by deriving closed-form expressions of the outage probability and detection error probability under CCI, considering that the wireless channels are characterized by Nakagami-mfading for UAV-to-ground links and Rayleigh fading for terrestrial links. Numerical results confirm the superior covertness of the proposed FJACC scheme over traditional non-friendly jammer aided transmission scheme. Furthermore, increasing the number of co-channel interferers or their transmit power exhibits a dual effect: it enhances covertness at the expense of reliability.

Multimodal large models have shown excellent ability in addressing image super-resolution in real-world scenarios by leveraging language class as condition information, yet their abilities in degraded images remain limited. In this paper, we first revisit the capabilities of the Recognize Anything Model (RAM) for degraded images by calculating text similarity. We find that directly using contrastive learning to fine-tune RAM in the degraded space is difficult to achieve acceptable results. To address this issue, we employ a degradation selection strategy to propose a Real Embedding Extractor (REE), which achieves significant recognition performance gain on degraded image content through contrastive learning. Furthermore, we use a Conditional Feature Modulator (CFM) to incorporate the high-level information of REE for a powerful Mamba-based network, which can leverage effective pixel information to restore image textures and produce visually pleasing results. Extensive experiments demonstrate that the REE can effectively help image super-resolution networks balance fidelity and perceptual quality, highlighting the great potential of Mamba in real-world applications. The source code of this work will be made publicly available at: https://github.com/nathan66666/DACESR.git.

With the rapid development of 5G networks, signaling network security has become increasingly critical. However, existing anomaly detection methods face significant limitations in handling Stream Control Transmission Protocol (SCTP)based signaling protocols, specifically the inherent ambiguity in distinguishing between normal and abnormal signaling patterns due to overlapping behavioral characteristics across different threat types. This paper proposes a comprehensive anomaly detection framework that integrates fuzzy clustering and association mining techniques to effectively resolve classification uncertainty in 5G signaling traffic analysis. The framework consists of three key components: (1) a 31-dimensional statistical feature characterization methodology specifically designed for SCTP and Next Generation Application Protocol (NGAP) protocols, (2) a fuzzy clustering analysis module that handles classification ambiguity through membership degree calculations, and (3) an association mining algorithm for automated threat type identification. Experimental evaluation on real 5G signaling datasets demonstrates superior performance compared to traditional clustering methods, with$8.3 \%-16.7 \%$improvement in classification accuracy. The framework successfully identifies five distinct threat categories while providing interpretable analysis for security practitioners.

Federated learning (FL) in Internet of Things (IoT) environments is impeded by model leakage, prohibitive computational overhead, and the lack of fair incentive mechanisms. To overcome these challenges,this paper proposes the PrivacyPreserving and Fair Payment framework based on Blockchain and Federated Learning (PPFP-BFL), a holistic architecture that synergistically integrates blockchain with federated learning. The framework's privacy is anchored by a novel Non-Interactive Functional Encryption (NIFE) scheme enhanced with SIMD technology, which secures model parameters with provable security and significantly reduced overhead. Concurrently, a novel incentive mechanism is established, transforming the blockchain from a passive ledger into an active arbitrator for fair exchange through automated, performance-based smart contracts. The framework's superiority and viability are validated by formal analysis and extensive experiments, which demonstrate a significant reduction in overhead against cryptographic-based solutions without sacrificing model accuracy.

This article investigates the physical-layer security (PLS) of a satellite-terrestrial integrated network (STIN) consisting of a satellite (S), a destination (D), and several friendly jammers in the presence of an eavesdropper (E). For improving PLS of the STIN, we propose three friendly jammer assisted communication schemes to help S securely send confidential information to D, i.e., the random jammer selection assisted communication (RJSC) scheme, the optimal jammer selection assisted communication (OJSC) scheme, and the multiple jammers assisted communication (MJC) scheme. For performance comparison, the nonjammer assisted communication (NJC) scheme is also presented. We analyze secrecy performance of the NJC, RJSC, OJSC, and MJC schemes by carrying out their closed-form secrecy outage probability (SOP) expressions, respectively. Numerical results unveil that the RJSC, OJSC, and MJC schemes exceed the NJC scheme with regard to their SOPs (e.g., as shown inFig. 2, when the signal-to-noise ratio is 25 dB, SOP of the STIN drops from 70% to 3%), and the OJSC scheme can get the best secrecy performance, showing the secrecy benefits of adopting friendly jammers assisted communication schemes against eavesdropping. Additionally, by increasing the number of friendly jammers, the secrecy performance of the OJSC and MJC schemes can be significantly enhanced, while that of the RJSC scheme remains unchanged.

In this paper, we investigate the security and reliability trade-off (SRT) for a wireless sensor network (WSN) which consists of one cluster head (CH), multiple users, and one eavesdropper (E), where the eavesdropper attempts to tap the confidential transmission between multiple users and CH. We first present two multiuser scheduling schemes, namely the selection combining (SC) scheme and the switch-and-examine combining with post-selection (SECps) scheme to enhance physical-layer security (PLS) of the WSN system. For comparison purposes, the round-robin scheduling (RRS) scheme is also considered as a baseline. Then, we analyze the SRT of the RRS, SECps, and SC schemes by deriving their closed-form outage and intercept probability expressions under the joint impact of hardware impairment (HI) and co-channel interference (CCI). And, secrecy diversity analysis of the three schemes is also carried out. Numerical results show that the SC and SECps scheme outperform the RRS scheme in terms of the SRT performance, where the SC scheme can achieve the best SRT performance at the cost of an increased channel estimation complexity. Moreover, a trade-off between the security and reliability can be achieved for each of the RRS, SECps, and SC schemes by adjusting the overall data rate and signal-to-noise ratio (SNR).

In this study, the authors investigate the security and reliability trade‐off (SRT) performance of a multiuser wireless network, where an eavesdropper attempts to overhear the confidential transmissions between a base station and multiple users under the impact of co‐channel interference. To enhance the SRT performance of the network, the authors propose two joint user and jammer selection schemes, namely the joint optimal user and random jammer selection (JOU‐RJS) scheme and the joint optimal user and optimal jammer selection (JOU‐OJS) scheme. For SRT performance comparison purposes, the traditional multiuser scheduling (TMUS) scheme is also considered. The authors derive closed‐form outage and intercept probability expressions for the JOU‐RJS and JOUOJS schemes. Simulation results show that the SRTs of both JOU‐RJS and JOU‐OJS schemes are better than that of the TMUS scheme, where JOU‐OJS achieves the best SRT performance. Additionally, this study also shows that an expected outage or intercept probability of the TMUS, JOU‐RJS, and JOU‐OJS schemes can be achieved by giving an appropriate overall rate. Finally, the sum of the outage and intercept probability can be minimised through an optimal power allocation between the selected user and friendly jammer for the proposed JOU‐RJS and JOU‐OJS.

In this paper, we analyze the secrecy outage probability and computation overhead of a multi-user multi-eavesdropper wireless system which is composed of one cluster head (CH) transmitting to multiple users, while multiple eavesdroppers attempt to tap the transmission from CH to multiple users in the presence of co-channel interference (CCI). To achieve high security and low computation overhead, we present two multi-user scheduling schemes, namely, the switch-and-examine combining with post-selection user scheduling (SECpsUS) scheme and the selection combining-based user scheduling (SCbUS) scheme. For the purpose of comparison, the conventional round-robin scheduling (RRS) is also considered as a benchmark scheme. Furthermore, we derive closed-form secrecy outage probability expressions and analyze computation overheads for the conventional RRS, SCbUS, and SECpsUS schemes. Numerical results and Monte Carlo simulations are provided to verify the correctness of our theoretical secrecy outage analysis and to demonstrate the effect of CCI on the system performance. It is shown that the SECpsUS and SCbUS schemes outperform the conventional RRS scheme in terms of their secrecy outage probabilities, where SCbUS achieves the best secrecy outage performance but at cost of the highest computation overhead, while the conventional RRS scheme has no computation overhead with the worst secrecy performance. Moreover, a flexible tradeoff between the secrecy outage performance and computation overhead can be achieved by the proposed SECpsUS scheme by adjusting a so-called switching threshold. In addition, as the number of users increases, the secrecy outage performance of the SECpsUS and SCbUS is improved significantly, whereas no secrecy benefit is achieved by the conventional RRS scheme.

In this paper, we study a multiuser uplink network consisting of one base station (BS), multiple users and one eavesdropper (E), where the users are intended to transmit their confidential messages to BS, while the eavesdropper attempts to tap their transmissions. To improve the transmission secrecy, we propose two friendly jammer selection-aided multiuser scheduling schemes, namely, the random jammer selection-aided multiuser scheduling (RJS-MUS) without knowing the eavesdropper's channel state information (CSI) and the optimal jammer selection-aided multiuser scheduling (OJS-MUS), where the CSIs of eavesdropper are available. For comparison purposes, the conventional non-jammer selection-aided multiuser scheduling (NJS-MUS) scheme is considered as a benchmark. We derive exact and asymptotic closed-form secrecy outage probability expressions for the conventional NJS-MUS as well as proposed RJS-MUS and OJS-MUS schemes. The numerical results show that the proposed RJS-MUS and OJS-MUS schemes with equal power allocation between the selected friendly jammer and scheduled user perform worse than the conventional NJS-MUS approach in terms of the secrecy outage probability in the low signal-to-noise ratio (SNR) region. As the SNR increases, the secrecy outage performance of RJS-MUS and OJS-MUS schemes substantially improves, which is, in turn, better than that of conventional NJS-MUS approach. Moreover, the secrecy advantage of RJS-MUS and OJS-MUS over NJS-MUS becomes more significant with an increasing SNR. Also, it is shown that for both the RJS-MUS and OJS-MUS schemes, a better secrecy performance can be achieved through an optimal power allocation (OPA) between the scheduled user and friendly jammer. In addition, the proposed RJS-MUS and OJS-MUS schemes with OPA strictly outperform the conventional NJS-MUS approach in terms of the secrecy outage probability.

In this paper, we consider a hybrid satellite- terrestrial relay network (HSTRN) composed of a geostationary satellite, a terrestrial destination and multiple terrestrial relays in the presence of an eavesdropper, where the satellite transmits its data to the terrestrial destination via decode-and- forward (DF) relays while the secure transmission from relay to destination may leak to the eavesdropper. We explore the physical-layer security against eavesdropping attacks in HSTRN and propose the optimal relay selection scheme for improving the transmission security. Additionally, the classic round-robin scheduling is also considered to a benchmark scheme. Furthermore, the closed-form expressions of secrecy outage probability for both the round-robin scheduling and optimal relay selection schemes are derived. Finally, numerical results show that our proposed scheme generally outperforms the round-robin scheduling in terms of the secrecy outage probability.

We explore the physical-layer security for a multisource multi-relay wireless network in the presence of an eavesdropper, in which one of multiple sources is scheduled to send its message to a destination with the assistance of multiple decode-and-forward (DF) relays. One eavesdropper is considered at the receiver side, and assumed to be capable of overhearing the transmission from relays to destination. In this paper, the round-robin scheduling and the joint source-relay selection schemes are presented to improve the physical-layer security of the multi-source multi-relay system, and their closedform intercept probability expressions are derived over Rayleigh fadingchannels.Numericalresultsdemonstratethattheproposed joint source-relay selection scheme achieves a better performance than the traditional round-robin scheduling in terms of the intercept probability.

Many published channel prediction algorithms focused on the narrow communication systems. In This work we propose a new prediction algorithm for wideband wireless communication systems. Since the frequency elements of channel response have the same correlation characteristic, this algorithm can compute their future frequency channel response with the same channel prediction coefficients based on a certain frequency element. Thanks to the good frequency property, this prediction algorithm only cost slight larger computation than that in flat fading channel. The final numeric results show the prediction performance and complexity of the prediction algorithm.