With the continuous development of information technology, privacy protection in the Internet of Things (IoT) has attracted people 's attention. This paper summarizes and discusses the privacy and security issues faced by various levels of the IoT, and proposes an overall framework for privacy and security protection; investigates the research progress of ABE search security in the IoT, summarizes the types of firmware implementation defects in the IoT, analyzes the typical defect generation mechanisms, and summarizes the existing firmware defect detection methods from the perspectives of static analysis , symbol execution, fuzzy testing, program validation, and machine learning ; analyzes the existing mainstream access control models in the IoT, and summarizes the issues that need to be addressed in the future for blockchain based access control in the IoT. It further studies the recent achievements and progress of machine learning in the security protection of the IoT, and summarizes the privacy laws, especially the information protection law of the European Union (EU) in enterprises. Finally, we propose the main challenges that current research still faces and point out the direction of future research development.

The rapid development of the social Internet of Things (IoT) enhances interconnectivity but also raises significant network security challenges, particularly from botnet attacks that disrupt system stability. Addressing this issue requires effective strategies to control botnet propagation in social IoT environments. This study develops a social IoT botnet propagation model incorporating social factors to analyze their influences on its propagation dynamics. Based on this, a social IoT botnet propagation control framework is constructed, formulating an optimization problem using Markov games. To solve the optimization problem, we propose SD-DRQN (Social-Dynamics Deep Recurrent Q-Network), a novel deep reinforcement learning algorithm that integrates Long Short-Term Memory (LSTM) layers to improve learning in dynamic social IoT environments. Experimental results validate the performance of the proposed SD-DRQN across various social IoT scenarios, including complex real-world topologies. The algorithm demonstrates faster convergence, superior generalization, and practical applicability, making it an effective solution for botnet propagation control in real-world social IoT deployments.

With the rapid development of IoT based on LoRa technology, the demand for LoRa-based indoor positioning has increased. This paper provides an overview of existing LoRa-based indoor fingerprint localization techniques. We first introduce the current status and principles of LoRa indoor positioning. Then we highlight the general process and key technologies of the fingerprint-based LoRa localization methods, including finger-print data acquisition, preprocessing, and localization algorithms. Through comprehensive analysis of LoRa indoor fingerprint localization technology, this paper aims to provide insights for researchers and promote further development and practical applications of LoRa technology.

The Internet of Things (IoT) is used in homes and hospitals and deployed outdoors to control and report environmental changes, prevent fires, and perform many more beneficial functions. However, all these benefits come at the tremendous risk of loss of privacy and security issues. To protect the IoT, much research has been carried out to address these risks and find better ways to eliminate them or at least minimize their impact on user privacy and security requirements. This paper expounds various network security risks faced by the IoT, analyzes their impacts, discusses risk assessment methods, shows the causes and hazards of these threats, and proposes an overall framework of privacy security protection. This paper summarizes the typical defect types in the implementation of IoT firmware, analyzes the generation mechanism of typical defects from the perspectives of fuzzy testing, program verification and machine learning, and compares and expounds the progress of security research for several common IoT protocols. This paper analyzes and summarizes the mainstream access control model in the existing IoT and the access control model after using the blockchain and builds a new integrated AIoT architecture for intelligent information processing. Finally, this paper expounds on the current legal development status of the privacy protection of network information in various countries and discusses the future prospects of the IoT.

To ensure an accurate power allocation against increasing intelligent jamming attacks on the offloading link of computation tasks, we investigate interactions between a cluster head node and an intelligent jammer using a Stackelberg game framework, under the constraint of the total power to use and the limited knowledge of its own channel gain for each player. In this game, the intelligent jammer gathers channel gain information and processes it using a deep neural network (DNN) to infer the accurate jamming power as an attack strategy. The cluster head node also exploits DNN to infer an accurate transmission power as a defense strategy according to the varying channel gain. We model the optimization of the attack and defense strategies using single channel jamming DNN (SJnet), multiple channel jamming DNN (MJnet), single channel sensor DNN (SSnet), and multiple channel sensor DNN (MSnet) for the single (multiple) channel jamming attacks. In addition, we extend the design to the scenario where the intelligent jammer can launch a hybrid mode jamming attack, and propose a DNN Stackelberg game-based defense scheme. Numerical simulation results demonstrate that our proposed mechanism is superior to other power allocation mechanisms under different scenarios in the sensor edge cloud.

In this paper, we investigate joint base station (BS) activation and beamforming design for coordinated downlink transmissions in a cellular heterogeneous network (HetNet). We formulate the total power minimization problem as a mixed integer program. Using the Benders' partitioning method and the convex duality theory, we show that the global optimal solution can then be computed by solving a sequence of relaxed master programs and the associated subproblems with affordable complexity.

Hostile jamming can cause significant performance degradation in wireless communications, but it also provides an unexplored source of additional signal power. In this letter, we propose an energy-harvesting receiver for two-way orthogonal frequency division multiplexing (OFDM) systems under hostile jamming. More specifically, in the downlink, the receiver is designed to simultaneously process information and harvest energy from the received desired signal as well as the jamming interference through a power splitter. The harvested energy can then be used as an additional source of power to enhance the uplink transmission. We investigate the optimal power allocation and power splitting ratio to maximize the sum-rate of the uplink and downlink transmissions. To reduce the complexity, a suboptimal energy harvesting scheme with closed-form solution is proposed. We also obtain a lower bound on the sum-rate of the proposed scheme under strong full-band jamming.

Energy harvesting is an emerging solution to prolong the lifetime of energy-constrained nodes in wireless networks. This letter develops a novel distributed energy beamforming scheme for realizing simultaneous wireless information and power transfer in the two-way relay channel (TWRC), where two source nodes exchange information via an energy-harvesting relay node. We investigate the optimal transceiver design to maximize the achievable sum-rate of the TWRC. We also propose a low-complexity power-splitting based suboptimal scheme with closed-form solution. Numerical results demonstrate significant performance improvement of the proposed schemes over the conventional power-splitting based scheme.

This paper considers malicious user detection and energy harvesting in orthogonal frequency division multiplexing-based cognitive radio networks under primary user emulation attack (PUEA). The digital TV (DTV) model adopted is the second generation terrestrial digital television standard (DVB-T2). In this paper, first, we propose an efficient advanced encryption standard (AES)-based DTV scheme, where the existing reference sequence used to generate the P2 pilot symbols in the DVB-T2 frames is encrypted using the AES algorithm to facilitate accurate primary user and malicious user detection. With the proposed scheme, we can detect PUEA accurately over all subcarriers or subbands where the P2 symbols present. Second, we come up with an effective communication scheme for the secondary users (SUs) under PUEA by exploiting the energy harvesting techniques. Optimal power splitting is considered for sum-rate maximization. As the optimal solution relies on multidimensional exhaustive search, we propose an effective suboptimal solution with much lower computational complexity. It is observed that the sum-rate of the SU network can be improved significantly with the energy harvesting technique. Third, we evaluate the worst case PUEA interference in terms of minimizing the sum-rate for the SUs. We show that for practical systems, as channel state information among the SUs is not available to the malicious user, the worst jamming for the SUs is when the malicious user performs equal power allocation over all the white space subcarriers. Simulation results are provided to illustrate the proposed approaches.

This paper considers transceiver design for the cellular two-way relay channel (cTWRC), where a multi-antenna base station (BS) exchanges information with multiple single-antenna mobile stations via a multi-antenna relay station. We propose a novel network coding scheme to approach the sum capacity of the cTWRC. Specifically, a new non-linear lattice-based precoding technique is proposed at the BS to pre-compensate the inter-stream interference, in order to allow efficient interference-free lattice decoding at the relay. We derive sufficient conditions for the proposed scheme to asymptotically achieve the sum capacity of the cTWRC in the high signal-to-noise ratio (SNR) regime. Numerical results show that the proposed scheme outperforms the existing schemes and is able to asymptotically achieve the cut-set bound of the cellular relay networks.

This paper considers jamming-resistant OFDM system design under full-band disguised jamming, where the jamming symbols are taken from the same constellation as the information symbols over each subcarrier. First, we analyze the impact of disguised jamming on OFDM systems. It is shown that due to the symmetricity between the authorized signal and jamming, the BER of OFDM systems without symbol-level precoding or only with repeated symbol-level coding is lower bounded by a modulation specific constant, which cannot be improved by increasing SNR. Second, we develop an optimal precoding scheme which minimizes the BER of OFDM systems under full-band disguised jamming. It is shown that the most efficient way to combat full-band disguised jamming in OFDM systems is to concentrate the total available power and distribute it uniformly over a particular number of subcarriers instead of the entire spectrum. The underlying argument is that for a particular subcarrier, when the signal-to-jamming ratio is large enough, then the receiver can distinguish the authorized signal from disguised jamming under the presence of noise. Both theoretical analysis and numerical results demonstrate that the BER performance of OFDM systems under full-band disguised jamming can be improved significantly with the proposed precoding scheme.

This paper introduces a class of perfect binary sequence pair (PBSP), which is characterized by the impulse-equivalent periodic autocorrelation function (PACF) and the length of N=2k. The proposed PBSP can be generated from a class of difference set pairs (DSP). Considering the desirable properties of the proposed sequence pair, orthogonal frequency division multiplexing (OFDM) transmission with time-domain superimposed training is proposed. Simulation results show that our binary sequence pair is ideal for channel estimation in terms of complexity, accuracy and efficiency.

Selection relaying is a promising technique for practical implementation of cooperative systems with multiple relays. However, to select the best relay, globe channel knowledge is required at the selecting entity. In this paper, we consider the relay selection problem in dual-hop amplify-and-forward (AF) communication systems with partial channel state information (CSI). We present relay selection strategies aiming at minimizing the outage probability with different kinds of channel knowledge available, including perfect, statistical and quantized CSI. Simulation results show that near optimal performance is achievable with a few bits feedback to the selecting entity. Thus the signaling overhead of relay selection can be greatly reduced with quantized CSI feedback.

In this paper, we investigate a radio resource allocation scheme for orthogonal frequency-division multiple-access (OFDMA)-based multiple-input multiple-output (MIMO) multihop networks. The half-duplex orthogonal relay channel construction method and related multihop transmission mechanism are designed to avoid the inter-hop interference. We propose a multistage resource allocation scheme for throughput maximization. And, the fairness consideration on sharing subcarriers among relay nodes is also discussed. Simulation results show that the spatial diversity gain offered by relay antenna array can effectively balance the tradeoff between the fairness performance and the system throughput. Results also show the proposed scheme is efficient with channel impairment when relay nodes are subject to severe shadowing effects.

Recent research has shown that differential transmission (DT) can be applied to STBC systems so that the receiver does not need channel state information (CSI) when compared to coherent detector. In this paper, we propose a generalized DT (GDT) scheme, which has a frame structure consisting of two parts, reference-block part and normal-block part. In contrast to the conventional DT (CDT) scheme, where each transmitted block is differentially encoded based on previous transmitted block, each GDT block in both of the two parts is differentially encoded based on previous reference block. It is shown that allocating more transmit power to the reference-block part leads to a more reliable reference for the differential detector. We discuss about the optimal power allocation between the reference-block part and the normal-block part. Simulation results show that the proposed GDT scheme achieves significant performance improvement over CDT and such performance can be very close to that of the coherent detection.

Distributed space time coding can achieve full spatial diversity in wireless relay networks. However, it requires accurate symbol-level synchronization and priori coordination between cooperative relay terminals, which is difficult to implement in distributed networks. In this paper, we propose a novel scheme based on interleaving to achieve cooperative diversity in both synchronous and asynchronous networks with little protocol overhead. A low complexity iterative detection algorithm is also proposed to combine signals from different relays at the receiver. The simulation results demonstrate the comparable performance to space-time codes based cooperative schemes which require perfect synchronization and coordination.

To address transmission problems encountered in WLAN environments, we propose a multi-user MIMO SDMA system based on the theory of convex optimization. With each user's BER as the cost function, we compute transmit and receive matrices to achieve optimal system performance. The proposed algorithm is assessed by simulations and is compared with conventional methods.